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fitcauto
構文
説明
fitcauto は、指定した予測子と応答データに基づいて、さまざまなハイパーパラメーターの値をもつ分類モデルのタイプの選択を自動的に試します。既定では、この関数は、ベイズ最適化を使用してモデルとそのハイパーパラメーターの値を選択し、各モデルの交差検証の分類誤差を計算します。最適化が完了すると、fitcauto は、データ セット全体で学習済みの、新しいデータの分類に最適であると予測したモデルを返します。返されたモデルのオブジェクト関数 predict と loss を使用して、新しいデータの分類、およびテスト セットの分類誤差の計算をそれぞれ行うことができます。
データに最適な分類器のタイプがわからない場合は、fitcauto を使用します。分類モデルのハイパーパラメーターを調整するための代替方法については、代替機能を参照してください。
データに含まれる観測値が 10,000 を超える場合は、fitcauto を実行するとき、ベイズ最適化の代わりに非同期連続半減アルゴリズム (ASHA) の使用を検討してください。データ セットの観測値が多いと、多くの場合、ベイズ最適化よりも ASHA 最適化の方が優れた解を速く見つけます。
Mdl = fitcauto(Tbl,ResponseVarName)Mdl を返します。テーブル Tbl には予測子変数と応答変数を格納します。ResponseVarName は応答変数の名前です。
Mdl = fitcauto(___,Name,Value)HyperparameterOptimizationOptions を使用して、ベイズ最適化 (既定) または非同期連続半減アルゴリズム (ASHA) を使用するかどうかを指定します。ASHA 最適化を使用するには、"HyperparameterOptimizationOptions",struct("Optimizer","asha") を指定します。この構造体に追加フィールドを含めて、その他の最適化の側面を制御できます。
[ は、Mdl,OptimizationResults] = fitcauto(___)OptimizationResults も返します。これには、モデル選択とハイパーパラメーター調整のプロセスの結果が含まれます。この出力は、ベイズ最適化を使用している場合は BayesianOptimization オブジェクトで、ASHA 最適化を使用している場合は table です。
例
table データを使用した分類器の自動選択
fitcauto を使用し、table で指定した予測子データと応答データに基づいて、最適化されたハイパーパラメーターをもつ分類モデルを自動的に選択します。
データの読み込み
carbig データ セットを読み込みます。このデータ セットには、1970 年代と 1980 年代初期に製造された自動車の測定値が格納されています。
load carbig米国製かどうかに基づいて、自動車を分類します。
Origin = categorical(cellstr(Origin)); Origin = mergecats(Origin,["France","Japan","Germany", ... "Sweden","Italy","England"],"NotUSA");
Acceleration、Displacement などの予測子変数と応答変数 Origin が格納された table を作成します。
cars = table(Acceleration,Displacement,Horsepower, ...
Model_Year,MPG,Weight,Origin);データの分割
データを学習セットとテスト セットに分割します。モデル選択とハイパーパラメーター調整のプロセスに観測値の約 80% を使用し、fitcauto によって返された最終モデルのパフォーマンスのテストに観測値の 20% を使用します。cvpartition を使用してデータを分割します。
rng("default") % For reproducibility of the data partition c = cvpartition(Origin,"Holdout",0.2); trainingIdx = training(c); % Training set indices carsTrain = cars(trainingIdx,:); testIdx = test(c); % Test set indices carsTest = cars(testIdx,:);
fitcauto の実行
学習データを fitcauto に渡します。既定では、fitcauto は、試行する適切なモデルのタイプを決定し、ベイズ最適化を使用して適切なハイパーパラメーター値を求め、パフォーマンスが最大となることが期待される学習済みモデル Mdl を返します。さらに、fitcauto は、最適化のプロット、および最適化の結果の反復表示を提供します。これらの結果を解釈する方法の詳細については、Verbose の表示を参照してください。
このプロセスにいくらか時間がかかることを見込んでください。Parallel Computing Toolbox™ のライセンスがある場合、最適化を並列で実行するよう指定して最適化プロセスを高速化することを検討してください。これを行うには、名前と値の引数 "HyperparameterOptimizationOptions",struct("UseParallel",true) を fitcauto に渡します。
Mdl = fitcauto(carsTrain,"Origin");Learner types to explore: ensemble, knn, nb, net, svm, tree Total iterations (MaxObjectiveEvaluations): 180 Total time (MaxTime): Inf |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 1 | Best | 0.10769 | 9.8867 | 0.10769 | 0.10769 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 291 | | | | | | | | | MinLeafSize: 4 | | 2 | Accept | 0.13231 | 8.4208 | 0.10769 | 0.12098 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 233 | | | | | | | | | MinLeafSize: 1 | | 3 | Best | 0.10154 | 0.46968 | 0.10154 | 0.10154 | tree | MinLeafSize: 5 | | 4 | Accept | 0.37231 | 0.77391 | 0.10154 | 0.10154 | svm | BoxConstraint: 0.22029 | | | | | | | | | KernelScale: 0.4534 | | 5 | Accept | 0.14769 | 0.12722 | 0.10154 | 0.12098 | tree | MinLeafSize: 2 | | 6 | Accept | 0.24308 | 0.54475 | 0.10154 | 0.12098 | knn | NumNeighbors: 155 | | 7 | Accept | 0.37231 | 0.17065 | 0.10154 | 0.12098 | svm | BoxConstraint: 22.3 | | | | | | | | | KernelScale: 0.018132 | | 8 | Accept | 0.19385 | 0.098037 | 0.10154 | 0.12098 | knn | NumNeighbors: 75 | | 9 | Accept | 0.15692 | 8.2932 | 0.10154 | 0.12098 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.0010226 | | | | | | | | | LayerSizes: 224 | | 10 | Accept | 0.37231 | 0.20214 | 0.10154 | 0.12098 | net | Activations: tanh | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 302.8 | | | | | | | | | LayerSizes: [ 78 5 ] | | 11 | Accept | 0.22769 | 1.2781 | 0.10154 | 0.12098 | nb | DistributionNames: kernel | | | | | | | | | Width: 214.96 | | | | | | | | | Standardize: false | | 12 | Accept | 0.18154 | 5.8459 | 0.10154 | 0.12323 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 232 | | | | | | | | | MinLeafSize: 105 | | 13 | Accept | 0.19692 | 0.090905 | 0.10154 | 0.12323 | knn | NumNeighbors: 13 | | 14 | Accept | 0.20308 | 0.10957 | 0.10154 | 0.12323 | svm | BoxConstraint: 9.1458 | | | | | | | | | KernelScale: 18.65 | | 15 | Accept | 0.14154 | 7.7326 | 0.10154 | 0.12323 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | MinLeafSize: 2 | | 16 | Accept | 0.11692 | 4.5938 | 0.10154 | 0.12323 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 214 | | | | | | | | | MinLeafSize: 1 | | 17 | Accept | 0.18462 | 0.088159 | 0.10154 | 0.12323 | knn | NumNeighbors: 10 | | 18 | Accept | 0.12308 | 0.077702 | 0.10154 | 0.12484 | tree | MinLeafSize: 10 | | 19 | Accept | 0.26462 | 3.68 | 0.10154 | 0.12484 | net | Activations: tanh | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 0.44352 | | | | | | | | | LayerSizes: [ 48 40 ] | | 20 | Accept | 0.10769 | 4.1582 | 0.10154 | 0.12484 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 206 | | | | | | | | | MinLeafSize: 3 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 21 | Accept | 0.12 | 0.092835 | 0.10154 | 0.12349 | tree | MinLeafSize: 13 | | 22 | Accept | 0.19385 | 0.08931 | 0.10154 | 0.12349 | knn | NumNeighbors: 57 | | 23 | Accept | 0.37231 | 0.29219 | 0.10154 | 0.12349 | net | Activations: relu | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 1.6049 | | | | | | | | | LayerSizes: [ 236 2 197 ] | | 24 | Accept | 0.13538 | 7.2642 | 0.10154 | 0.12349 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 272 | | | | | | | | | MinLeafSize: 4 | | 25 | Accept | 0.21231 | 0.12119 | 0.10154 | 0.12349 | svm | BoxConstraint: 3.2832 | | | | | | | | | KernelScale: 19.127 | | 26 | Accept | 0.23692 | 0.088582 | 0.10154 | 0.12349 | knn | NumNeighbors: 154 | | 27 | Accept | 0.18154 | 0.071505 | 0.10154 | 0.12413 | tree | MinLeafSize: 30 | | 28 | Accept | 0.22769 | 0.14963 | 0.10154 | 0.12413 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 29 | Accept | 0.37231 | 0.31305 | 0.10154 | 0.12413 | net | Activations: tanh | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 9.7449 | | | | | | | | | LayerSizes: [ 123 213 22 ] | | 30 | Accept | 0.22769 | 0.061021 | 0.10154 | 0.12413 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 31 | Accept | 0.20615 | 7.6661 | 0.10154 | 0.12413 | net | Activations: sigmoid | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 9.0476e-06 | | | | | | | | | LayerSizes: [ 1 286 ] | | 32 | Accept | 0.37231 | 0.12123 | 0.10154 | 0.12413 | net | Activations: none | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 169.93 | | | | | | | | | LayerSizes: [ 8 43 ] | | 33 | Accept | 0.16923 | 0.053687 | 0.10154 | 0.12413 | tree | MinLeafSize: 50 | | 34 | Accept | 0.12923 | 0.052139 | 0.10154 | 0.12413 | tree | MinLeafSize: 3 | | 35 | Accept | 0.37538 | 0.16254 | 0.10154 | 0.12413 | svm | BoxConstraint: 31.988 | | | | | | | | | KernelScale: 0.068262 | | 36 | Best | 0.086154 | 5.1664 | 0.086154 | 0.11432 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 259 | | | | | | | | | MinLeafSize: 46 | | 37 | Accept | 0.20308 | 0.093464 | 0.086154 | 0.11432 | knn | NumNeighbors: 7 | | 38 | Accept | 0.19692 | 0.062179 | 0.086154 | 0.11432 | knn | NumNeighbors: 9 | | 39 | Accept | 0.21846 | 0.20379 | 0.086154 | 0.11432 | nb | DistributionNames: kernel | | | | | | | | | Width: 11.43 | | | | | | | | | Standardize: false | | 40 | Accept | 0.22769 | 0.077831 | 0.086154 | 0.11432 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 41 | Accept | 0.24615 | 0.2016 | 0.086154 | 0.11432 | nb | DistributionNames: kernel | | | | | | | | | Width: 0.95982 | | | | | | | | | Standardize: false | | 42 | Accept | 0.22769 | 0.054205 | 0.086154 | 0.11432 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 43 | Accept | 0.16308 | 1.8399 | 0.086154 | 0.11432 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 8.2888e-08 | | | | | | | | | LayerSizes: 20 | | 44 | Accept | 0.37231 | 0.10773 | 0.086154 | 0.11432 | svm | BoxConstraint: 0.5593 | | | | | | | | | KernelScale: 0.003667 | | 45 | Accept | 0.11385 | 0.075454 | 0.086154 | 0.11432 | tree | MinLeafSize: 11 | | 46 | Accept | 0.20308 | 0.074108 | 0.086154 | 0.11432 | knn | NumNeighbors: 7 | | 47 | Accept | 0.22769 | 0.061325 | 0.086154 | 0.11432 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 48 | Accept | 0.25231 | 5.6001 | 0.086154 | 0.11432 | net | Activations: sigmoid | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 4.2329e-05 | | | | | | | | | LayerSizes: [ 16 21 86 ] | | 49 | Accept | 0.22769 | 0.051748 | 0.086154 | 0.11432 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 50 | Accept | 0.37231 | 0.11468 | 0.086154 | 0.11432 | svm | BoxConstraint: 47.547 | | | | | | | | | KernelScale: 0.038904 | | 51 | Accept | 0.16923 | 0.074099 | 0.086154 | 0.11432 | tree | MinLeafSize: 76 | | 52 | Accept | 0.15692 | 1.6882 | 0.086154 | 0.11432 | net | Activations: tanh | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 0.24612 | | | | | | | | | LayerSizes: 6 | | 53 | Accept | 0.10462 | 4.0245 | 0.086154 | 0.10962 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 211 | | | | | | | | | MinLeafSize: 6 | | 54 | Accept | 0.11385 | 0.092927 | 0.086154 | 0.10962 | tree | MinLeafSize: 11 | | 55 | Accept | 0.086154 | 5.1988 | 0.086154 | 0.098594 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 286 | | | | | | | | | MinLeafSize: 47 | | 56 | Accept | 0.19692 | 0.075963 | 0.086154 | 0.098594 | knn | NumNeighbors: 28 | | 57 | Accept | 0.12 | 0.070258 | 0.086154 | 0.098594 | tree | MinLeafSize: 4 | | 58 | Accept | 0.2 | 0.068373 | 0.086154 | 0.098594 | knn | NumNeighbors: 3 | | 59 | Accept | 0.37231 | 0.15296 | 0.086154 | 0.098594 | net | Activations: tanh | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 79.211 | | | | | | | | | LayerSizes: 1 | | 60 | Accept | 0.19692 | 0.061209 | 0.086154 | 0.098594 | knn | NumNeighbors: 13 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 61 | Accept | 0.37231 | 5.3523 | 0.086154 | 0.10784 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 234 | | | | | | | | | MinLeafSize: 155 | | 62 | Accept | 0.21846 | 0.076683 | 0.086154 | 0.10784 | knn | NumNeighbors: 2 | | 63 | Accept | 0.32308 | 1.0531 | 0.086154 | 0.10784 | net | Activations: none | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 0.00049454 | | | | | | | | | LayerSizes: [ 3 145 ] | | 64 | Accept | 0.11077 | 5.6836 | 0.086154 | 0.10698 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 300 | | | | | | | | | MinLeafSize: 1 | | 65 | Accept | 0.19692 | 2.5205 | 0.086154 | 0.10698 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 1.1014e-05 | | | | | | | | | LayerSizes: [ 26 2 ] | | 66 | Accept | 0.12 | 0.072271 | 0.086154 | 0.10698 | tree | MinLeafSize: 4 | | 67 | Accept | 0.21846 | 0.095838 | 0.086154 | 0.10698 | knn | NumNeighbors: 2 | | 68 | Accept | 0.37231 | 0.091219 | 0.086154 | 0.10698 | svm | BoxConstraint: 0.0061987 | | | | | | | | | KernelScale: 31.312 | | 69 | Accept | 0.37231 | 0.064588 | 0.086154 | 0.10698 | svm | BoxConstraint: 0.070644 | | | | | | | | | KernelScale: 0.22263 | | 70 | Accept | 0.37538 | 0.082788 | 0.086154 | 0.10698 | svm | BoxConstraint: 9.2391 | | | | | | | | | KernelScale: 0.062892 | | 71 | Accept | 0.15692 | 0.061431 | 0.086154 | 0.10698 | svm | BoxConstraint: 32.735 | | | | | | | | | KernelScale: 1.3401 | | 72 | Accept | 0.31077 | 0.05396 | 0.086154 | 0.10698 | svm | BoxConstraint: 0.0407 | | | | | | | | | KernelScale: 3.4118 | | 73 | Accept | 0.37231 | 0.053805 | 0.086154 | 0.10698 | svm | BoxConstraint: 0.0019745 | | | | | | | | | KernelScale: 62.689 | | 74 | Accept | 0.13538 | 5.1971 | 0.086154 | 0.10699 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 205 | | | | | | | | | MinLeafSize: 3 | | 75 | Accept | 0.22769 | 0.068918 | 0.086154 | 0.10699 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 76 | Accept | 0.37231 | 0.06363 | 0.086154 | 0.10699 | svm | BoxConstraint: 0.42987 | | | | | | | | | KernelScale: 234.78 | | 77 | Accept | 0.25846 | 0.2272 | 0.086154 | 0.10699 | nb | DistributionNames: kernel | | | | | | | | | Width: 2.2007 | | | | | | | | | Standardize: false | | 78 | Accept | 0.13846 | 5.0838 | 0.086154 | 0.10344 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 207 | | | | | | | | | MinLeafSize: 4 | | 79 | Accept | 0.14462 | 0.071561 | 0.086154 | 0.10344 | tree | MinLeafSize: 21 | | 80 | Accept | 0.37231 | 0.097395 | 0.086154 | 0.10344 | svm | BoxConstraint: 176.96 | | | | | | | | | KernelScale: 0.022732 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 81 | Accept | 0.19692 | 0.07841 | 0.086154 | 0.10344 | knn | NumNeighbors: 9 | | 82 | Accept | 0.26154 | 0.17034 | 0.086154 | 0.10344 | nb | DistributionNames: kernel | | | | | | | | | Width: 2.808 | | | | | | | | | Standardize: false | | 83 | Accept | 0.37231 | 0.18007 | 0.086154 | 0.10344 | nb | DistributionNames: kernel | | | | | | | | | Width: 615.95 | | | | | | | | | Standardize: true | | 84 | Accept | 0.26154 | 1.8058 | 0.086154 | 0.10344 | net | Activations: relu | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 8.2545e-08 | | | | | | | | | LayerSizes: [ 57 2 7 ] | | 85 | Accept | 0.22769 | 0.063696 | 0.086154 | 0.10344 | nb | DistributionNames: normal | | | | | | | | | Width: NaN | | | | | | | | | Standardize: - | | 86 | Accept | 0.14769 | 6.2743 | 0.086154 | 0.10769 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 252 | | | | | | | | | MinLeafSize: 32 | | 87 | Accept | 0.17231 | 0.06519 | 0.086154 | 0.10769 | tree | MinLeafSize: 126 | | 88 | Accept | 0.16923 | 0.043935 | 0.086154 | 0.10769 | tree | MinLeafSize: 93 | | 89 | Accept | 0.22769 | 0.18302 | 0.086154 | 0.10769 | nb | DistributionNames: kernel | | | | | | | | | Width: 0.43629 | | | | | | | | | Standardize: false | | 90 | Accept | 0.26462 | 3.9886 | 0.086154 | 0.10769 | net | Activations: sigmoid | | | | | | | | | Standardize: false | | | | | | | | | Lambda: 7.2789e-07 | | | | | | | | | LayerSizes: 98 | | 91 | Accept | 0.098462 | 4.8539 | 0.086154 | 0.10445 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 259 | | | | | | | | | MinLeafSize: 39 | | 92 | Accept | 0.11077 | 4.9109 | 0.086154 | 0.099362 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 273 | | | | | | | | | MinLeafSize: 70 | | 93 | Accept | 0.13846 | 5.1708 | 0.086154 | 0.10034 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 281 | | | | | | | | | MinLeafSize: 84 | | 94 | Accept | 0.12615 | 4.9036 | 0.086154 | 0.099454 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 244 | | | | | | | | | MinLeafSize: 76 | | 95 | Accept | 0.11077 | 5.5508 | 0.086154 | 0.097618 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 285 | | | | | | | | | MinLeafSize: 71 | | 96 | Accept | 0.14154 | 4.4952 | 0.086154 | 0.095919 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 245 | | | | | | | | | MinLeafSize: 57 | | 97 | Accept | 0.095385 | 4.815 | 0.086154 | 0.094528 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 260 | | | | | | | | | MinLeafSize: 51 | | 98 | Accept | 0.12308 | 4.6592 | 0.086154 | 0.093172 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 260 | | | | | | | | | MinLeafSize: 77 | | 99 | Accept | 0.37231 | 4.8941 | 0.086154 | 0.094437 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 268 | | | | | | | | | MinLeafSize: 149 | | 100 | Accept | 0.13538 | 5.2577 | 0.086154 | 0.096586 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 295 | | | | | | | | | MinLeafSize: 92 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 101 | Accept | 0.092308 | 4.4168 | 0.086154 | 0.092045 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 247 | | | | | | | | | MinLeafSize: 43 | | 102 | Accept | 0.13846 | 4.8009 | 0.086154 | 0.093381 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 265 | | | | | | | | | MinLeafSize: 90 | | 103 | Accept | 0.089231 | 4.393 | 0.086154 | 0.091453 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 245 | | | | | | | | | MinLeafSize: 48 | | 104 | Accept | 0.098462 | 4.7966 | 0.086154 | 0.091605 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 265 | | | | | | | | | MinLeafSize: 52 | | 105 | Accept | 0.086154 | 4.9362 | 0.086154 | 0.090054 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 276 | | | | | | | | | MinLeafSize: 47 | | 106 | Accept | 0.089231 | 4.1084 | 0.086154 | 0.088948 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 224 | | | | | | | | | MinLeafSize: 45 | | 107 | Accept | 0.13538 | 5.0023 | 0.086154 | 0.089673 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 279 | | | | | | | | | MinLeafSize: 97 | | 108 | Accept | 0.13538 | 5.0726 | 0.086154 | 0.089434 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 284 | | | | | | | | | MinLeafSize: 99 | | 109 | Accept | 0.14154 | 3.9115 | 0.086154 | 0.089922 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 214 | | | | | | | | | MinLeafSize: 99 | | 110 | Accept | 0.089231 | 5.324 | 0.086154 | 0.089121 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 296 | | | | | | | | | MinLeafSize: 47 | | 111 | Accept | 0.18154 | 5.2688 | 0.086154 | 0.088882 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 293 | | | | | | | | | MinLeafSize: 124 | | 112 | Accept | 0.13231 | 4.3796 | 0.086154 | 0.088506 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 247 | | | | | | | | | MinLeafSize: 54 | | 113 | Accept | 0.098462 | 3.9631 | 0.086154 | 0.087879 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 219 | | | | | | | | | MinLeafSize: 51 | | 114 | Accept | 0.11077 | 5.0266 | 0.086154 | 0.088112 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | MinLeafSize: 28 | | 115 | Accept | 0.098462 | 5.1256 | 0.086154 | 0.089033 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 286 | | | | | | | | | MinLeafSize: 37 | | 116 | Accept | 0.089231 | 5.3373 | 0.086154 | 0.08886 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 298 | | | | | | | | | MinLeafSize: 47 | | 117 | Accept | 0.086154 | 4.9772 | 0.086154 | 0.087554 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 273 | | | | | | | | | MinLeafSize: 47 | | 118 | Accept | 0.095385 | 4.9785 | 0.086154 | 0.087693 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 276 | | | | | | | | | MinLeafSize: 46 | | 119 | Accept | 0.086154 | 5.4771 | 0.086154 | 0.087702 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 283 | | | | | | | | | MinLeafSize: 49 | | 120 | Accept | 0.092308 | 3.7618 | 0.086154 | 0.087509 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 205 | | | | | | | | | MinLeafSize: 47 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 121 | Accept | 0.10462 | 4.2801 | 0.086154 | 0.087866 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 236 | | | | | | | | | MinLeafSize: 52 | | 122 | Accept | 0.37231 | 0.10976 | 0.086154 | 0.087866 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.72122 | | | | | | | | | LayerSizes: 13 | | 123 | Accept | 0.37231 | 0.10272 | 0.086154 | 0.087866 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.43917 | | | | | | | | | LayerSizes: 2 | | 124 | Accept | 0.2 | 0.12343 | 0.086154 | 0.087866 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.050009 | | | | | | | | | LayerSizes: 6 | | 125 | Accept | 0.29231 | 0.12056 | 0.086154 | 0.087866 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.30341 | | | | | | | | | LayerSizes: 8 | | 126 | Accept | 0.089231 | 4.654 | 0.086154 | 0.087499 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 259 | | | | | | | | | MinLeafSize: 48 | | 127 | Accept | 0.086154 | 5.012 | 0.086154 | 0.086595 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 282 | | | | | | | | | MinLeafSize: 49 | | 128 | Accept | 0.18154 | 4.9285 | 0.086154 | 0.08742 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 282 | | | | | | | | | MinLeafSize: 124 | | 129 | Accept | 0.086154 | 5.1215 | 0.086154 | 0.087394 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 277 | | | | | | | | | MinLeafSize: 49 | | 130 | Accept | 0.086154 | 4.8293 | 0.086154 | 0.086574 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 270 | | | | | | | | | MinLeafSize: 49 | | 131 | Accept | 0.13846 | 4.2622 | 0.086154 | 0.086693 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 239 | | | | | | | | | MinLeafSize: 104 | | 132 | Accept | 0.14154 | 4.4707 | 0.086154 | 0.086428 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 252 | | | | | | | | | MinLeafSize: 104 | | 133 | Accept | 0.37231 | 0.23993 | 0.086154 | 0.086428 | net | Activations: tanh | | | | | | | | | Standardize: true | | | | | | | | | Lambda: 0.15163 | | | | | | | | | LayerSizes: [ 20 93 ] | | 134 | Best | 0.083077 | 4.9394 | 0.083077 | 0.085629 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 275 | | | | | | | | | MinLeafSize: 49 | | 135 | Accept | 0.086154 | 4.7512 | 0.083077 | 0.08537 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 266 | | | | | | | | | MinLeafSize: 49 | | 136 | Accept | 0.089231 | 4.1396 | 0.083077 | 0.085748 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 228 | | | | | | | | | MinLeafSize: 49 | | 137 | Accept | 0.14154 | 4.5844 | 0.083077 | 0.08557 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 263 | | | | | | | | | MinLeafSize: 110 | | 138 | Accept | 0.089231 | 4.1878 | 0.083077 | 0.085505 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 233 | | | | | | | | | MinLeafSize: 49 | | 139 | Accept | 0.15385 | 6.4706 | 0.083077 | 0.085674 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 273 | | | | | | | | | MinLeafSize: 49 | | 140 | Accept | 0.17538 | 6.311 | 0.083077 | 0.08568 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 271 | | | | | | | | | MinLeafSize: 106 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 141 | Accept | 0.083077 | 5.0683 | 0.083077 | 0.085124 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 275 | | | | | | | | | MinLeafSize: 49 | | 142 | Accept | 0.083077 | 4.9466 | 0.083077 | 0.084346 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 272 | | | | | | | | | MinLeafSize: 49 | | 143 | Accept | 0.18462 | 4.0363 | 0.083077 | 0.084296 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 227 | | | | | | | | | MinLeafSize: 115 | | 144 | Accept | 0.098462 | 4.8689 | 0.083077 | 0.084396 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 271 | | | | | | | | | MinLeafSize: 50 | | 145 | Accept | 0.17231 | 0.11083 | 0.083077 | 0.084396 | svm | BoxConstraint: 7.4019 | | | | | | | | | KernelScale: 0.98931 | | 146 | Accept | 0.21538 | 0.059402 | 0.083077 | 0.084396 | svm | BoxConstraint: 17.066 | | | | | | | | | KernelScale: 0.77684 | | 147 | Accept | 0.086154 | 4.8705 | 0.083077 | 0.084203 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 271 | | | | | | | | | MinLeafSize: 48 | | 148 | Accept | 0.086154 | 4.8211 | 0.083077 | 0.084345 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 270 | | | | | | | | | MinLeafSize: 49 | | 149 | Accept | 0.37231 | 0.063284 | 0.083077 | 0.084345 | svm | BoxConstraint: 41.79 | | | | | | | | | KernelScale: 281.24 | | 150 | Accept | 0.21846 | 0.06502 | 0.083077 | 0.084345 | svm | BoxConstraint: 59.071 | | | | | | | | | KernelScale: 0.64404 | | 151 | Accept | 0.21231 | 0.058461 | 0.083077 | 0.084345 | svm | BoxConstraint: 27.03 | | | | | | | | | KernelScale: 0.58467 | | 152 | Accept | 0.16 | 0.054338 | 0.083077 | 0.084345 | svm | BoxConstraint: 1.0872 | | | | | | | | | KernelScale: 1.1762 | | 153 | Accept | 0.17846 | 0.055672 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.55409 | | | | | | | | | KernelScale: 1.0383 | | 154 | Accept | 0.37231 | 0.056181 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.002375 | | | | | | | | | KernelScale: 1.1605 | | 155 | Accept | 0.16923 | 0.057591 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.5264 | | | | | | | | | KernelScale: 1.7249 | | 156 | Accept | 0.16308 | 0.076268 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.4426 | | | | | | | | | KernelScale: 1.3849 | | 157 | Accept | 0.16308 | 0.071124 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.43171 | | | | | | | | | KernelScale: 1.2674 | | 158 | Accept | 0.17231 | 0.059062 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.33464 | | | | | | | | | KernelScale: 1.3315 | | 159 | Accept | 0.19385 | 0.069434 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.15356 | | | | | | | | | KernelScale: 1.9858 | | 160 | Accept | 0.20308 | 0.057155 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.1477 | | | | | | | | | KernelScale: 1.5045 | |=============================================================================================================================================| | Iter | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | result | loss | & validation (sec)| validation loss | validation loss | | | |=============================================================================================================================================| | 161 | Accept | 0.23692 | 0.062405 | 0.083077 | 0.084345 | svm | BoxConstraint: 0.42828 | | | | | | | | | KernelScale: 14.853 | | 162 | Accept | 0.086154 | 5.1922 | 0.083077 | 0.084288 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 275 | | | | | | | | | MinLeafSize: 47 | | 163 | Accept | 0.083077 | 5.2334 | 0.083077 | 0.084062 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 287 | | | | | | | | | MinLeafSize: 49 | | 164 | Accept | 0.20923 | 0.066873 | 0.083077 | 0.084062 | svm | BoxConstraint: 1.6705 | | | | | | | | | KernelScale: 0.51936 | | 165 | Accept | 0.083077 | 4.8932 | 0.083077 | 0.083699 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 274 | | | | | | | | | MinLeafSize: 48 | | 166 | Accept | 0.086154 | 5.2371 | 0.083077 | 0.083963 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 296 | | | | | | | | | MinLeafSize: 49 | | 167 | Accept | 0.37231 | 0.067167 | 0.083077 | 0.083963 | svm | BoxConstraint: 0.0024433 | | | | | | | | | KernelScale: 1.378 | | 168 | Accept | 0.32923 | 0.067094 | 0.083077 | 0.083963 | svm | BoxConstraint: 0.62588 | | | | | | | | | KernelScale: 0.49029 | | 169 | Accept | 0.19077 | 0.068847 | 0.083077 | 0.083963 | svm | BoxConstraint: 0.2494 | | | | | | | | | KernelScale: 1.2705 | | 170 | Accept | 0.24 | 0.055606 | 0.083077 | 0.083963 | svm | BoxConstraint: 0.85565 | | | | | | | | | KernelScale: 0.50742 | | 171 | Accept | 0.12923 | 3.9215 | 0.083077 | 0.083927 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 218 | | | | | | | | | MinLeafSize: 53 | | 172 | Accept | 0.11077 | 5.1249 | 0.083077 | 0.083981 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 283 | | | | | | | | | MinLeafSize: 34 | | 173 | Accept | 0.37231 | 6.449 | 0.083077 | 0.083855 | ensemble | Method: Bag | | | | | | | | | NumLearningCycles: 298 | | | | | | | | | MinLeafSize: 137 | | 174 | Accept | 0.20615 | 4.7277 | 0.083077 | 0.083837 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 263 | | | | | | | | | MinLeafSize: 128 | | 175 | Best | 0.083077 | 4.9307 | 0.083077 | 0.083627 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 274 | | | | | | | | | MinLeafSize: 44 | | 176 | Accept | 0.089231 | 4.9299 | 0.083077 | 0.083892 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 274 | | | | | | | | | MinLeafSize: 45 | | 177 | Accept | 0.092308 | 4.9475 | 0.083077 | 0.083668 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 274 | | | | | | | | | MinLeafSize: 52 | | 178 | Accept | 0.086154 | 5.237 | 0.083077 | 0.08391 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 291 | | | | | | | | | MinLeafSize: 49 | | 179 | Accept | 0.083077 | 4.8488 | 0.083077 | 0.08378 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 272 | | | | | | | | | MinLeafSize: 49 | | 180 | Accept | 0.083077 | 4.9095 | 0.083077 | 0.083649 | ensemble | Method: LogitBoost | | | | | | | | | NumLearningCycles: 274 | | | | | | | | | MinLeafSize: 48 | __________________________________________________________ Optimization completed. Total iterations: 180 Total elapsed time: 624.9642 seconds Total time for training and validation: 456.1613 seconds Best observed learner is an ensemble model with: Learner: ensemble Method: LogitBoost NumLearningCycles: 274 MinLeafSize: 44 Observed validation loss: 0.083077 Time for training and validation: 4.9307 seconds Best estimated learner (returned model) is an ensemble model with: Learner: ensemble Method: LogitBoost NumLearningCycles: 275 MinLeafSize: 49 Estimated validation loss: 0.083649 Estimated time for training and validation: 5.0351 seconds Documentation for fitcauto display
fitcauto によって返される最終的なモデルが、最適な推定学習器となります。モデルを返す前に、関数は学習データ全体 (carsTrain)、リストされている Learner (またはモデル) のタイプ、および表示されたハイパーパラメーター値を使用して、モデルの再学習を行います。
テスト セットのパフォーマンスの評価
テスト セットに対するモデルのパフォーマンスを評価します。
testAccuracy = 1 - loss(Mdl,carsTest,"Origin")testAccuracy = 0.9389
confusionchart(carsTest.Origin,predict(Mdl,carsTest))
行列データを使用した分類器の自動選択
fitcauto を使用し、個別の変数で指定した予測子データと応答データに基づいて、最適化されたハイパーパラメーターをもつ分類モデルを自動的に選択します。
データの読み込み
humanactivity データ セットを読み込みます。このデータ セットには、人間の次の 5 種類の身体動作についての 24,075 個の観測値が含まれています。座る (1)、立つ (2)、歩く (3)、走る (4)、踊る (5)。各観測値には、スマートフォンの加速度センサーによって測定された加速度データから抽出した 60 個の特徴量が含まれています。変数 feat には、24,075 個の観測値に関する 60 個の特徴量から成る予測子データ行列が格納され、応答変数 actid には、観測値の身体動作 ID が整数として格納されています。
load humanactivityデータの分割
データを学習セットとテスト セットに分割します。モデルの選択に観測値の 90% を使用し、fitcauto によって返された最終モデルの検証に観測値の 10% を使用します。cvpartition を使用して、観測値の 10% をテスト用に確保します。
rng("default") % For reproducibility of the partition c = cvpartition(actid,"Holdout",0.10); trainingIndices = training(c); % Indices for the training set XTrain = feat(trainingIndices,:); YTrain = actid(trainingIndices); testIndices = test(c); % Indices for the test set XTest = feat(testIndices,:); YTest = actid(testIndices);
fitcauto の実行
学習データを fitcauto に渡します。学習データ XTrain に含まれる観測値が 10,000 を超えるため、ベイズ最適化ではなく ASHA 最適化を使用します。関数 fitcauto は、さまざまなハイパーパラメーターの値をもつ適切なモデル (または学習器) のタイプを無作為に選択し、学習データの小さいサブセットでこのモデルに学習させ、適切に機能するモデルをプロモートして、プロモートされたモデルを徐々に大きくした学習データのセットで再学習させます。この関数は、最適な交差検証性能をもち、すべての学習データで再学習済みのモデル、および最適化の詳細を含む table を返します。最適化を並列実行するよう指定します (Parallel Computing Toolbox™ が必要)。
既定の設定では、fitcauto は、最適化のプロット、および最適化の結果の反復表示を提供します。これらの結果を解釈する方法の詳細については、Verbose の表示を参照してください。
options = struct("Optimizer","asha","UseParallel",true); [Mdl,OptimizationResults] = fitcauto(XTrain,YTrain,"HyperparameterOptimizationOptions",options);
Starting parallel pool (parpool) using the 'Processes' profile ... 19-Sep-2023 09:24:41: Job Running. Waiting for parallel pool workers to connect ... Connected to parallel pool with 6 workers. Copying objective function to workers... Done copying objective function to workers. Learner types to explore: ensemble, knn, nb, net, svm, tree Total iterations (MaxObjectiveEvaluations): 595 Total time (MaxTime): Inf |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 1 | 6 | Best | 0.74165 | 4.0088 | 0.74165 | 271 | tree | MinLeafSize: 2491 | | 2 | 6 | Best | 0.1223 | 7.6549 | 0.1223 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.13184 | | | | | | | | | | KernelScale: 8.4782 | | 3 | 6 | Best | 0.046336 | 12.627 | 0.046336 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 158.32 | | | | | | | | | | KernelScale: 6.4649 | | 4 | 6 | Accept | 0.74155 | 9.2316 | 0.046336 | 271 | knn | NumNeighbors: 212 | | 5 | 6 | Accept | 0.74165 | 6.9383 | 0.046336 | 271 | knn | NumNeighbors: 598 | | 6 | 6 | Best | 0.025152 | 6.9363 | 0.025152 | 1084 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 158.32 | | | | | | | | | | KernelScale: 6.4649 | | 7 | 6 | Accept | 0.74165 | 17.111 | 0.025152 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 266 | | | | | | | | | | MinLeafSize: 1441 | | | | | | | | | | MaxNumSplits: 53 | | 8 | 6 | Accept | 0.30266 | 17.643 | 0.025152 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 4.8317e-08 | | | | | | | | | | LayerSizes: [ 57 2 3 ] | | 9 | 6 | Accept | 0.048735 | 3.7155 | 0.025152 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.6516e-06 | | | | | | | | | | LayerSizes: [ 59 27 ] | | 10 | 6 | Accept | 0.73906 | 15.207 | 0.025152 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.0060924 | | | | | | | | | | KernelScale: 0.0031147 | | 11 | 6 | Accept | 0.74165 | 5.6809 | 0.025152 | 271 | knn | NumNeighbors: 1879 | | 12 | 6 | Accept | 0.74165 | 6.9374 | 0.025152 | 271 | knn | NumNeighbors: 5201 | | 13 | 6 | Accept | 0.74165 | 2.414 | 0.025152 | 271 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 4.5028e-08 | | | | | | | | | | LayerSizes: [ 38 1 ] | | 14 | 6 | Best | 0.023168 | 6.8641 | 0.023168 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.6516e-06 | | | | | | | | | | LayerSizes: [ 59 27 ] | | 15 | 6 | Accept | 0.74165 | 0.54204 | 0.023168 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.0523 | | | | | | | | | | LayerSizes: [ 22 1 ] | | 16 | 6 | Accept | 0.057504 | 1.2855 | 0.023168 | 271 | knn | NumNeighbors: 3 | | 17 | 6 | Accept | 0.059442 | 5.06 | 0.023168 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.13184 | | | | | | | | | | KernelScale: 8.4782 | | 18 | 6 | Accept | 0.10333 | 1.3616 | 0.023168 | 271 | tree | MinLeafSize: 33 | | 19 | 6 | Accept | 0.11187 | 3.1181 | 0.023168 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.041107 | | | | | | | | | | KernelScale: 65.57 | | 20 | 6 | Accept | 0.033875 | 17.589 | 0.023168 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 213 | | | | | | | | | | MinLeafSize: 12 | | | | | | | | | | MaxNumSplits: 65 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 21 | 6 | Accept | 0.16914 | 28.952 | 0.023168 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 7.0496e-07 | | | | | | | | | | LayerSizes: [ 1 300 ] | | 22 | 6 | Accept | 0.034936 | 3.9056 | 0.023168 | 1084 | knn | NumNeighbors: 3 | | 23 | 6 | Accept | 0.056535 | 1.0202 | 0.023168 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 9.9716e-10 | | | | | | | | | | LayerSizes: 2 | | 24 | 6 | Accept | 0.058981 | 1.0248 | 0.023168 | 271 | knn | NumNeighbors: 2 | | 25 | 6 | Accept | 0.73902 | 15.251 | 0.023168 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.017494 | | | | | | | | | | KernelScale: 0.015797 | | 26 | 6 | Accept | 0.037152 | 8.6076 | 0.023168 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.026e-05 | | | | | | | | | | LayerSizes: 32 | | 27 | 6 | Accept | 0.026998 | 22.18 | 0.023168 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | | MinLeafSize: 15 | | | | | | | | | | MaxNumSplits: 23 | | 28 | 6 | Accept | 0.055612 | 3.1266 | 0.023168 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 3.248 | | | | | | | | | | KernelScale: 41.255 | | 29 | 6 | Accept | 0.74165 | 13.828 | 0.023168 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.00197 | | | | | | | | | | KernelScale: 0.019161 | | 30 | 6 | Accept | 0.046105 | 1.9398 | 0.023168 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 823.07 | | | | | | | | | | KernelScale: 10.178 | | 31 | 6 | Accept | 0.74165 | 12.366 | 0.023168 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 245 | | | | | | | | | | MinLeafSize: 654 | | | | | | | | | | MaxNumSplits: 91 | | 32 | 6 | Accept | 0.028475 | 24.979 | 0.023168 | 1084 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 213 | | | | | | | | | | MinLeafSize: 12 | | | | | | | | | | MaxNumSplits: 65 | | 33 | 6 | Accept | 0.071811 | 1.6409 | 0.023168 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 34 | 6 | Accept | 0.046474 | 29.788 | 0.023168 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.016435 | | | | | | | | | | LayerSizes: 273 | | 35 | 6 | Best | 0.015737 | 30.935 | 0.015737 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | | MinLeafSize: 15 | | | | | | | | | | MaxNumSplits: 23 | | 36 | 6 | Accept | 0.063319 | 1.7339 | 0.015737 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 37 | 6 | Accept | 0.053489 | 0.88882 | 0.015737 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 38 | 6 | Accept | 0.73957 | 11.218 | 0.015737 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 596 | | | | | | | | | | KernelScale: 0.0057402 | | 39 | 6 | Accept | 0.022429 | 2.3673 | 0.015737 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 823.07 | | | | | | | | | | KernelScale: 10.178 | | 40 | 6 | Accept | 0.68197 | 4.8353 | 0.015737 | 271 | knn | NumNeighbors: 182 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 41 | 5 | Best | 0.011769 | 46.391 | 0.011769 | 4334 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.6516e-06 | | | | | | | | | | LayerSizes: [ 59 27 ] | | 42 | 5 | Accept | 0.037798 | 17.137 | 0.011769 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.026e-05 | | | | | | | | | | LayerSizes: 32 | | 43 | 6 | Accept | 0.74165 | 6.2665 | 0.011769 | 271 | knn | NumNeighbors: 4666 | | 44 | 6 | Accept | 0.11819 | 2.9796 | 0.011769 | 271 | knn | NumNeighbors: 39 | | 45 | 6 | Accept | 0.038859 | 13.517 | 0.011769 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0010532 | | | | | | | | | | LayerSizes: 73 | | 46 | 6 | Accept | 0.74165 | 9.2963 | 0.011769 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 218 | | | | | | | | | | MinLeafSize: 845 | | | | | | | | | | MaxNumSplits: 11 | | 47 | 6 | Accept | 0.035998 | 1.4159 | 0.011769 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 223 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 75 | | 48 | 6 | Accept | 0.74165 | 0.37391 | 0.011769 | 271 | tree | MinLeafSize: 6998 | | 49 | 6 | Accept | 0.11593 | 0.46269 | 0.011769 | 271 | tree | MinLeafSize: 60 | | 50 | 6 | Accept | 0.019014 | 10.885 | 0.011769 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 223 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 75 | | 51 | 6 | Accept | 0.73615 | 8.4139 | 0.011769 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.0031837 | | | | | | | | | | KernelScale: 0.29449 | | 52 | 6 | Accept | 0.74165 | 3.9499 | 0.011769 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.010385 | | | | | | | | | | KernelScale: 94.31 | | 53 | 6 | Accept | 0.026029 | 28.896 | 0.011769 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0010532 | | | | | | | | | | LayerSizes: 73 | | 54 | 6 | Accept | 0.060319 | 0.81631 | 0.011769 | 271 | tree | MinLeafSize: 12 | | 55 | 6 | Best | 0.0089533 | 41.428 | 0.0089533 | 4334 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | | MinLeafSize: 15 | | | | | | | | | | MaxNumSplits: 23 | | 56 | 6 | Accept | 0.06738 | 0.91477 | 0.0089533 | 271 | tree | MinLeafSize: 20 | | 57 | 6 | Accept | 0.036321 | 5.7009 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0002263 | | | | | | | | | | LayerSizes: 177 | | 58 | 6 | Accept | 0.045966 | 2.5476 | 0.0089533 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 696.44 | | | | | | | | | | KernelScale: 12.469 | | 59 | 6 | Accept | 0.74165 | 5.2545 | 0.0089533 | 271 | knn | NumNeighbors: 9924 | | 60 | 6 | Accept | 0.025522 | 15.396 | 0.0089533 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 222 | | | | | | | | | | MinLeafSize: 11 | | | | | | | | | | MaxNumSplits: 10 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 61 | 6 | Accept | 0.73874 | 10.999 | 0.0089533 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.0024804 | | | | | | | | | | KernelScale: 0.023469 | | 62 | 6 | Accept | 0.018183 | 18.263 | 0.0089533 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 222 | | | | | | | | | | MinLeafSize: 11 | | | | | | | | | | MaxNumSplits: 10 | | 63 | 6 | Accept | 0.74165 | 0.55103 | 0.0089533 | 271 | tree | MinLeafSize: 310 | | 64 | 6 | Accept | 0.045182 | 0.85215 | 0.0089533 | 271 | tree | MinLeafSize: 5 | | 65 | 6 | Accept | 0.74086 | 11.228 | 0.0089533 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.43772 | | | | | | | | | | KernelScale: 0.0096446 | | 66 | 6 | Accept | 0.49788 | 10.925 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 8.9349e-08 | | | | | | | | | | LayerSizes: [ 1 82 ] | | 67 | 6 | Accept | 0.050028 | 2.3543 | 0.0089533 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.5558e-06 | | | | | | | | | | LayerSizes: [ 81 35 ] | | 68 | 6 | Accept | 0.74165 | 5.3103 | 0.0089533 | 271 | knn | NumNeighbors: 2746 | | 69 | 6 | Accept | 0.74091 | 11.227 | 0.0089533 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.48674 | | | | | | | | | | KernelScale: 0.004356 | | 70 | 6 | Accept | 0.047951 | 1.5672 | 0.0089533 | 1084 | tree | MinLeafSize: 5 | | 71 | 6 | Accept | 0.019568 | 31.464 | 0.0089533 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0002263 | | | | | | | | | | LayerSizes: 177 | | 72 | 6 | Accept | 0.2015 | 2.7997 | 0.0089533 | 271 | knn | NumNeighbors: 68 | | 73 | 6 | Accept | 0.049705 | 7.6929 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.012071 | | | | | | | | | | LayerSizes: [ 37 6 ] | | 74 | 6 | Accept | 0.043474 | 76.24 | 0.0089533 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.016435 | | | | | | | | | | LayerSizes: 273 | | 75 | 6 | Accept | 0.072042 | 1.4239 | 0.0089533 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 76 | 6 | Accept | 0.33007 | 3.9175 | 0.0089533 | 271 | knn | NumNeighbors: 128 | | 77 | 6 | Accept | 0.023491 | 2.7736 | 0.0089533 | 1084 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 696.44 | | | | | | | | | | KernelScale: 12.469 | | 78 | 6 | Accept | 0.013476 | 25.8 | 0.0089533 | 4334 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 222 | | | | | | | | | | MinLeafSize: 11 | | | | | | | | | | MaxNumSplits: 10 | | 79 | 6 | Accept | 0.1876 | 183.18 | 0.0089533 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 4.7771 | | | | | | | | | | Standardize: true | | 80 | 6 | Accept | 0.73888 | 12.408 | 0.0089533 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 11.435 | | | | | | | | | | KernelScale: 0.099759 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 81 | 6 | Accept | 0.090641 | 1.7902 | 0.0089533 | 271 | knn | NumNeighbors: 14 | | 82 | 6 | Accept | 0.74165 | 5.5707 | 0.0089533 | 271 | knn | NumNeighbors: 1886 | | 83 | 6 | Accept | 0.046013 | 20.62 | 0.0089533 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.012071 | | | | | | | | | | LayerSizes: [ 37 6 ] | | 84 | 6 | Accept | 0.72471 | 178.93 | 0.0089533 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 725.08 | | | | | | | | | | Standardize: false | | 85 | 6 | Accept | 0.066504 | 3.7768 | 0.0089533 | 271 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.025101 | | | | | | | | | | LayerSizes: [ 8 5 ] | | 86 | 6 | Accept | 0.13795 | 2.7947 | 0.0089533 | 271 | knn | NumNeighbors: 38 | | 87 | 6 | Accept | 0.10024 | 178.01 | 0.0089533 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 7.237 | | | | | | | | | | Standardize: false | | 88 | 6 | Accept | 0.022476 | 8.0228 | 0.0089533 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.5558e-06 | | | | | | | | | | LayerSizes: [ 81 35 ] | | 89 | 6 | Accept | 0.078411 | 8.0896 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 9.3779e-06 | | | | | | | | | | LayerSizes: [ 44 1 ] | | 90 | 6 | Accept | 0.050812 | 1.0009 | 0.0089533 | 271 | knn | NumNeighbors: 1 | | 91 | 6 | Accept | 0.094656 | 2.4365 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 5.5224e-05 | | | | | | | | | | LayerSizes: [ 2 4 ] | | 92 | 6 | Accept | 0.66947 | 68.845 | 0.0089533 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.001962 | | | | | | | | | | Standardize: true | | 93 | 6 | Accept | 0.1013 | 2.7144 | 0.0089533 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.25014 | | | | | | | | | | KernelScale: 13.411 | | 94 | 6 | Accept | 0.036967 | 3.334 | 0.0089533 | 1084 | knn | NumNeighbors: 1 | | 95 | 6 | Accept | 0.10481 | 1.8344 | 0.0089533 | 271 | knn | NumNeighbors: 30 | | 96 | 6 | Accept | 0.062304 | 3.5505 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 7.7047e-10 | | | | | | | | | | LayerSizes: 36 | | 97 | 6 | Accept | 0.063042 | 1.0809 | 0.0089533 | 271 | knn | NumNeighbors: 5 | | 98 | 6 | Accept | 0.051089 | 0.99813 | 0.0089533 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 99 | 6 | Accept | 0.74165 | 5.1444 | 0.0089533 | 271 | knn | NumNeighbors: 348 | | 100 | 6 | Accept | 0.074395 | 0.892 | 0.0089533 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 101 | 6 | Accept | 0.73417 | 2.7528 | 0.0089533 | 271 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 4.7256e-08 | | | | | | | | | | LayerSizes: [ 2 5 ] | | 102 | 6 | Accept | 0.0097379 | 48.336 | 0.0089533 | 4334 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 223 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 75 | | 103 | 6 | Accept | 0.74165 | 5.3769 | 0.0089533 | 271 | knn | NumNeighbors: 4201 | | 104 | 6 | Accept | 0.037244 | 3.4366 | 0.0089533 | 1084 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 3.248 | | | | | | | | | | KernelScale: 41.255 | | 105 | 6 | Accept | 0.74165 | 5.323 | 0.0089533 | 271 | knn | NumNeighbors: 287 | | 106 | 6 | Accept | 0.3166 | 3.4868 | 0.0089533 | 271 | knn | NumNeighbors: 120 | | 107 | 6 | Accept | 0.075042 | 1.9 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.043564 | | | | | | | | | | LayerSizes: 69 | | 108 | 6 | Accept | 0.068442 | 15.243 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 6.1116e-09 | | | | | | | | | | LayerSizes: [ 14 169 ] | | 109 | 6 | Accept | 0.057596 | 6.0808 | 0.0089533 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 9.9716e-10 | | | | | | | | | | LayerSizes: 2 | | 110 | 6 | Accept | 0.06858 | 0.67371 | 0.0089533 | 271 | tree | MinLeafSize: 22 | | 111 | 6 | Accept | 0.74165 | 4.9853 | 0.0089533 | 271 | knn | NumNeighbors: 6033 | | 112 | 6 | Accept | 0.087595 | 1.3138 | 0.0089533 | 271 | knn | NumNeighbors: 10 | | 113 | 6 | Accept | 0.058889 | 2.0479 | 0.0089533 | 271 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.11135 | | | | | | | | | | LayerSizes: 60 | | 114 | 6 | Accept | 0.049982 | 4.0713 | 0.0089533 | 1084 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.11135 | | | | | | | | | | LayerSizes: 60 | | 115 | 6 | Accept | 0.74165 | 0.12699 | 0.0089533 | 271 | tree | MinLeafSize: 265 | | 116 | 6 | Accept | 0.079703 | 1.1773 | 0.0089533 | 271 | knn | NumNeighbors: 6 | | 117 | 6 | Accept | 0.063273 | 11.955 | 0.0089533 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 6.6414e-09 | | | | | | | | | | LayerSizes: [ 87 9 ] | | 118 | 6 | Accept | 0.062673 | 0.75061 | 0.0089533 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 119 | 6 | Accept | 0.038444 | 3.1736 | 0.0089533 | 1084 | knn | NumNeighbors: 2 | | 120 | 6 | Accept | 0.74165 | 0.1229 | 0.0089533 | 271 | tree | MinLeafSize: 859 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 121 | 6 | Accept | 0.053212 | 0.79281 | 0.0089533 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 122 | 6 | Best | 0.0060458 | 72.662 | 0.0060458 | 17335 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 278 | | | | | | | | | | MinLeafSize: 15 | | | | | | | | | | MaxNumSplits: 23 | | 123 | 6 | Accept | 0.082195 | 1.3834 | 0.0060458 | 271 | knn | NumNeighbors: 10 | | 124 | 6 | Accept | 0.73085 | 7.9395 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 6.257 | | | | | | | | | | KernelScale: 0.37274 | | 125 | 6 | Accept | 0.055474 | 0.7295 | 0.0060458 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 126 | 6 | Accept | 0.35278 | 177.85 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 8.9008 | | | | | | | | | | Standardize: true | | 127 | 6 | Accept | 0.054735 | 0.77186 | 0.0060458 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 128 | 6 | Accept | 0.014307 | 6.7912 | 0.0060458 | 4334 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 823.07 | | | | | | | | | | KernelScale: 10.178 | | 129 | 6 | Accept | 0.037475 | 1.4301 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 187.62 | | | | | | | | | | KernelScale: 55.462 | | 130 | 6 | Accept | 0.73943 | 11.852 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 1.6685 | | | | | | | | | | KernelScale: 0.0010585 | | 131 | 6 | Accept | 0.047397 | 3.5417 | 0.0060458 | 271 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.4668e-06 | | | | | | | | | | LayerSizes: [ 3 8 ] | | 132 | 6 | Accept | 0.026952 | 2.0123 | 0.0060458 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 187.62 | | | | | | | | | | KernelScale: 55.462 | | 133 | 6 | Accept | 0.74165 | 0.43116 | 0.0060458 | 271 | tree | MinLeafSize: 708 | | 134 | 6 | Accept | 0.74165 | 0.36963 | 0.0060458 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 1.9349 | | | | | | | | | | LayerSizes: 2 | | 135 | 6 | Accept | 0.14145 | 2.0682 | 0.0060458 | 271 | knn | NumNeighbors: 41 | | 136 | 6 | Accept | 0.55547 | 170.51 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 157.05 | | | | | | | | | | Standardize: false | | 137 | 6 | Accept | 0.040751 | 8.1074 | 0.0060458 | 1084 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.4668e-06 | | | | | | | | | | LayerSizes: [ 3 8 ] | | 138 | 6 | Accept | 0.031706 | 14.615 | 0.0060458 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 226 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 74 | | 139 | 6 | Accept | 0.73902 | 11.589 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.41508 | | | | | | | | | | KernelScale: 0.1675 | | 140 | 6 | Accept | 0.74165 | 8.2111 | 0.0060458 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 219 | | | | | | | | | | MinLeafSize: 6163 | | | | | | | | | | MaxNumSplits: 42 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 141 | 6 | Accept | 0.074119 | 6.8044 | 0.0060458 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00025944 | | | | | | | | | | LayerSizes: [ 55 2 ] | | 142 | 6 | Accept | 0.74165 | 5.0555 | 0.0060458 | 271 | knn | NumNeighbors: 5959 | | 143 | 6 | Accept | 0.74165 | 167.44 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 75.452 | | | | | | | | | | Standardize: true | | 144 | 6 | Accept | 0.1175 | 2.8353 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.060918 | | | | | | | | | | KernelScale: 3.9775 | | 145 | 6 | Accept | 0.052843 | 0.92716 | 0.0060458 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 146 | 6 | Accept | 0.20334 | 2.636 | 0.0060458 | 271 | knn | NumNeighbors: 69 | | 147 | 6 | Accept | 0.064565 | 0.92349 | 0.0060458 | 271 | knn | NumNeighbors: 1 | | 148 | 6 | Accept | 0.02566 | 21.599 | 0.0060458 | 1084 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 226 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 74 | | 149 | 6 | Accept | 0.73939 | 11.582 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.85756 | | | | | | | | | | KernelScale: 0.022404 | | 150 | 6 | Accept | 0.012507 | 137.79 | 0.0060458 | 4334 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0002263 | | | | | | | | | | LayerSizes: 177 | | 151 | 6 | Accept | 0.74165 | 0.20624 | 0.0060458 | 271 | tree | MinLeafSize: 589 | | 152 | 6 | Accept | 0.73888 | 11.909 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.085214 | | | | | | | | | | KernelScale: 0.019894 | | 153 | 6 | Accept | 0.04389 | 1.5349 | 0.0060458 | 1084 | tree | MinLeafSize: 12 | | 154 | 6 | Accept | 0.74165 | 5.1888 | 0.0060458 | 271 | knn | NumNeighbors: 7024 | | 155 | 6 | Accept | 0.74165 | 0.12894 | 0.0060458 | 271 | tree | MinLeafSize: 1833 | | 156 | 6 | Accept | 0.70182 | 62.43 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.0010713 | | | | | | | | | | Standardize: false | | 157 | 6 | Accept | 0.73966 | 12.02 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 5.4071 | | | | | | | | | | KernelScale: 0.0034099 | | 158 | 6 | Accept | 0.04232 | 1.4806 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 28.455 | | | | | | | | | | KernelScale: 18.848 | | 159 | 6 | Accept | 0.73943 | 12.42 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 258.99 | | | | | | | | | | KernelScale: 0.001158 | | 160 | 6 | Accept | 0.74165 | 10.635 | 0.0060458 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 216 | | | | | | | | | | MinLeafSize: 179 | | | | | | | | | | MaxNumSplits: 17 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 161 | 6 | Accept | 0.025522 | 2.5412 | 0.0060458 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 28.455 | | | | | | | | | | KernelScale: 18.848 | | 162 | 6 | Accept | 0.11635 | 0.60355 | 0.0060458 | 271 | tree | MinLeafSize: 38 | | 163 | 6 | Accept | 0.74165 | 13.755 | 0.0060458 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 255 | | | | | | | | | | MinLeafSize: 2676 | | | | | | | | | | MaxNumSplits: 25 | | 164 | 6 | Accept | 0.039182 | 20.787 | 0.0060458 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 7.7047e-10 | | | | | | | | | | LayerSizes: 36 | | 165 | 6 | Accept | 0.066365 | 0.74225 | 0.0060458 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 166 | 6 | Accept | 0.73315 | 9.6689 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 137.09 | | | | | | | | | | KernelScale: 0.3904 | | 167 | 6 | Accept | 0.74165 | 5.2573 | 0.0060458 | 271 | knn | NumNeighbors: 895 | | 168 | 6 | Accept | 0.072688 | 2.3768 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 6.6815 | | | | | | | | | | KernelScale: 87.965 | | 169 | 6 | Accept | 0.05492 | 0.95631 | 0.0060458 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 170 | 6 | Accept | 0.045459 | 1.5197 | 0.0060458 | 271 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00026079 | | | | | | | | | | LayerSizes: [ 63 29 ] | | 171 | 6 | Accept | 0.011999 | 4.2993 | 0.0060458 | 4334 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 696.44 | | | | | | | | | | KernelScale: 12.469 | | 172 | 6 | Accept | 0.049797 | 6.8403 | 0.0060458 | 271 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00025954 | | | | | | | | | | LayerSizes: [ 13 93 8 ] | | 173 | 6 | Accept | 0.036644 | 5.0611 | 0.0060458 | 1084 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00026079 | | | | | | | | | | LayerSizes: [ 63 29 ] | | 174 | 6 | Accept | 0.52968 | 0.27159 | 0.0060458 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.17331 | | | | | | | | | | LayerSizes: 1 | | 175 | 6 | Accept | 0.73943 | 10.824 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 53.188 | | | | | | | | | | KernelScale: 0.0038378 | | 176 | 6 | Accept | 0.26015 | 3.0267 | 0.0060458 | 271 | knn | NumNeighbors: 96 | | 177 | 6 | Accept | 0.078918 | 0.84112 | 0.0060458 | 271 | tree | MinLeafSize: 2 | | 178 | 6 | Accept | 0.74165 | 10.331 | 0.0060458 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 246 | | | | | | | | | | MinLeafSize: 5299 | | | | | | | | | | MaxNumSplits: 20 | | 179 | 6 | Accept | 0.74165 | 0.29554 | 0.0060458 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 3.0257 | | | | | | | | | | LayerSizes: [ 7 6 ] | | 180 | 6 | Accept | 0.01163 | 66.58 | 0.0060458 | 4334 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.5558e-06 | | | | | | | | | | LayerSizes: [ 81 35 ] | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 181 | 6 | Accept | 0.026906 | 16.117 | 0.0060458 | 1084 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00025954 | | | | | | | | | | LayerSizes: [ 13 93 8 ] | | 182 | 6 | Accept | 0.73911 | 10.811 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 256.67 | | | | | | | | | | KernelScale: 0.0062547 | | 183 | 6 | Accept | 0.06798 | 0.74847 | 0.0060458 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 184 | 6 | Accept | 0.038075 | 3.5466 | 0.0060458 | 1084 | knn | NumNeighbors: 5 | | 185 | 6 | Accept | 0.74165 | 10.67 | 0.0060458 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 267 | | | | | | | | | | MinLeafSize: 1066 | | | | | | | | | | MaxNumSplits: 92 | | 186 | 6 | Accept | 0.74165 | 5.1586 | 0.0060458 | 271 | knn | NumNeighbors: 10321 | | 187 | 6 | Accept | 0.036736 | 9.109 | 0.0060458 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 286 | | | | | | | | | | MinLeafSize: 2 | | | | | | | | | | MaxNumSplits: 15 | | 188 | 6 | Accept | 0.091148 | 2.3089 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 23.004 | | | | | | | | | | KernelScale: 173.23 | | 189 | 6 | Accept | 0.11653 | 3.6349 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.12558 | | | | | | | | | | KernelScale: 11.544 | | 190 | 6 | Accept | 0.054966 | 0.84721 | 0.0060458 | 271 | tree | MinLeafSize: 2 | | 191 | 6 | Accept | 0.13407 | 0.42209 | 0.0060458 | 271 | tree | MinLeafSize: 66 | | 192 | 6 | Accept | 0.3273 | 3.3821 | 0.0060458 | 271 | knn | NumNeighbors: 119 | | 193 | 6 | Accept | 0.047305 | 1.6523 | 0.0060458 | 1084 | tree | MinLeafSize: 2 | | 194 | 6 | Accept | 0.6511 | 65.478 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.0025491 | | | | | | | | | | Standardize: true | | 195 | 6 | Accept | 0.74165 | 0.097407 | 0.0060458 | 271 | tree | MinLeafSize: 1197 | | 196 | 6 | Accept | 0.013245 | 7.1848 | 0.0060458 | 4334 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 158.32 | | | | | | | | | | KernelScale: 6.4649 | | 197 | 6 | Accept | 0.74165 | 4.1289 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.11328 | | | | | | | | | | KernelScale: 94.294 | | 198 | 6 | Accept | 0.062212 | 0.83367 | 0.0060458 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 199 | 6 | Accept | 0.054274 | 0.74717 | 0.0060458 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 200 | 6 | Accept | 0.37068 | 0.73189 | 0.0060458 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0056781 | | | | | | | | | | LayerSizes: [ 21 8 ] | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 201 | 6 | Accept | 0.74165 | 5.2012 | 0.0060458 | 271 | knn | NumNeighbors: 688 | | 202 | 6 | Accept | 0.74165 | 171.35 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 85.472 | | | | | | | | | | Standardize: true | | 203 | 6 | Accept | 0.014999 | 26.441 | 0.0060458 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 286 | | | | | | | | | | MinLeafSize: 2 | | | | | | | | | | MaxNumSplits: 15 | | 204 | 6 | Accept | 0.065211 | 0.75381 | 0.0060458 | 271 | tree | MinLeafSize: 15 | | 205 | 6 | Accept | 0.73888 | 11.931 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.011927 | | | | | | | | | | KernelScale: 0.026341 | | 206 | 6 | Accept | 0.74165 | 9.9001 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.32733 | | | | | | | | | | KernelScale: 0.23652 | | 207 | 6 | Accept | 0.064796 | 0.75371 | 0.0060458 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 208 | 6 | Accept | 0.74165 | 5.1131 | 0.0060458 | 271 | knn | NumNeighbors: 2107 | | 209 | 6 | Accept | 0.050582 | 0.7812 | 0.0060458 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 210 | 6 | Accept | 0.74165 | 0.14087 | 0.0060458 | 271 | tree | MinLeafSize: 4153 | | 211 | 6 | Accept | 0.14819 | 116.63 | 0.0060458 | 271 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.043528 | | | | | | | | | | Standardize: true | | 212 | 6 | Accept | 0.031013 | 18.505 | 0.0060458 | 271 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 281 | | | | | | | | | | MinLeafSize: 6 | | | | | | | | | | MaxNumSplits: 17 | | 213 | 6 | Accept | 0.74165 | 5.1385 | 0.0060458 | 271 | knn | NumNeighbors: 3140 | | 214 | 6 | Accept | 0.74165 | 10.367 | 0.0060458 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.0012596 | | | | | | | | | | KernelScale: 0.018258 | | 215 | 6 | Accept | 0.73925 | 11.902 | 0.0060458 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.15181 | | | | | | | | | | KernelScale: 0.032095 | | 216 | 6 | Accept | 0.11473 | 13.752 | 0.0060458 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.9472e-07 | | | | | | | | | | LayerSizes: [ 5 150 ] | | 217 | 6 | Accept | 0.083995 | 1.7133 | 0.0060458 | 271 | knn | NumNeighbors: 21 | | 218 | 6 | Accept | 0.036321 | 37.146 | 0.0060458 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 6.6414e-09 | | | | | | | | | | LayerSizes: [ 87 9 ] | | 219 | 6 | Best | 0.0038305 | 92.541 | 0.0038305 | 17335 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 223 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 75 | | 220 | 6 | Accept | 0.037752 | 3.6943 | 0.0038305 | 1084 | knn | NumNeighbors: 1 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 221 | 6 | Accept | 0.04352 | 1.5953 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 637.73 | | | | | | | | | | KernelScale: 110.65 | | 222 | 6 | Accept | 0.72586 | 4.3773 | 0.0038305 | 271 | knn | NumNeighbors: 186 | | 223 | 6 | Accept | 0.74165 | 12.694 | 0.0038305 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 296 | | | | | | | | | | MinLeafSize: 564 | | | | | | | | | | MaxNumSplits: 37 | | 224 | 6 | Accept | 0.05192 | 1.976 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 20.629 | | | | | | | | | | KernelScale: 59.563 | | 225 | 6 | Accept | 0.03069 | 28.311 | 0.0038305 | 1084 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 281 | | | | | | | | | | MinLeafSize: 6 | | | | | | | | | | MaxNumSplits: 17 | | 226 | 6 | Accept | 0.027737 | 2.1774 | 0.0038305 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 637.73 | | | | | | | | | | KernelScale: 110.65 | | 227 | 6 | Accept | 0.071949 | 0.93703 | 0.0038305 | 271 | tree | MinLeafSize: 4 | | 228 | 6 | Accept | 0.73754 | 5.2323 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.16605 | | | | | | | | | | KernelScale: 1.961 | | 229 | 6 | Accept | 0.031983 | 2.224 | 0.0038305 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 212 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 13 | | 230 | 6 | Accept | 0.060181 | 0.81105 | 0.0038305 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 231 | 6 | Accept | 0.31115 | 4.0247 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 664.88 | | | | | | | | | | KernelScale: 1.8095 | | 232 | 6 | Accept | 0.044628 | 12.596 | 0.0038305 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0013677 | | | | | | | | | | LayerSizes: [ 61 16 ] | | 233 | 6 | Accept | 0.19406 | 4.1139 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.044961 | | | | | | | | | | KernelScale: 7.539 | | 234 | 6 | Accept | 0.060596 | 0.65038 | 0.0038305 | 271 | tree | MinLeafSize: 19 | | 235 | 6 | Accept | 0.022983 | 17.528 | 0.0038305 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 287 | | | | | | | | | | MinLeafSize: 3 | | | | | | | | | | MaxNumSplits: 34 | | 236 | 6 | Accept | 0.014953 | 18.564 | 0.0038305 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 212 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 13 | | 237 | 6 | Accept | 0.009461 | 37.045 | 0.0038305 | 4334 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 286 | | | | | | | | | | MinLeafSize: 2 | | | | | | | | | | MaxNumSplits: 15 | | 238 | 6 | Accept | 0.087964 | 0.76386 | 0.0038305 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 239 | 6 | Accept | 0.74165 | 4.9599 | 0.0038305 | 271 | knn | NumNeighbors: 240 | | 240 | 6 | Accept | 0.7392 | 10.444 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 75.297 | | | | | | | | | | KernelScale: 0.0026183 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 241 | 6 | Accept | 0.74165 | 10.385 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.046006 | | | | | | | | | | KernelScale: 0.050465 | | 242 | 6 | Accept | 0.029629 | 30.9 | 0.0038305 | 1084 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0013677 | | | | | | | | | | LayerSizes: [ 61 16 ] | | 243 | 6 | Accept | 0.74165 | 4.9502 | 0.0038305 | 271 | knn | NumNeighbors: 4241 | | 244 | 6 | Accept | 0.012184 | 24.176 | 0.0038305 | 4334 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 212 | | | | | | | | | | MinLeafSize: 1 | | | | | | | | | | MaxNumSplits: 13 | | 245 | 6 | Accept | 0.43493 | 6.3714 | 0.0038305 | 271 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.059029 | | | | | | | | | | LayerSizes: [ 67 76 253 ] | | 246 | 6 | Accept | 0.74165 | 0.78817 | 0.0038305 | 271 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.17963 | | | | | | | | | | LayerSizes: [ 221 2 11 ] | | 247 | 6 | Accept | 0.034013 | 2.7876 | 0.0038305 | 1084 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 20.629 | | | | | | | | | | KernelScale: 59.563 | | 248 | 6 | Accept | 0.74165 | 0.32674 | 0.0038305 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.1834 | | | | | | | | | | LayerSizes: [ 1 24 ] | | 249 | 6 | Accept | 0.73948 | 12.098 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 816.76 | | | | | | | | | | KernelScale: 0.0011285 | | 250 | 6 | Accept | 0.73888 | 10.6 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 5.3104 | | | | | | | | | | KernelScale: 0.032781 | | 251 | 6 | Accept | 0.05192 | 3.7149 | 0.0038305 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 8.9184e-06 | | | | | | | | | | LayerSizes: [ 12 173 ] | | 252 | 6 | Accept | 0.1619 | 3.8251 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 503.88 | | | | | | | | | | KernelScale: 2.0431 | | 253 | 6 | Accept | 0.016014 | 31.54 | 0.0038305 | 1084 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 287 | | | | | | | | | | MinLeafSize: 3 | | | | | | | | | | MaxNumSplits: 34 | | 254 | 6 | Accept | 0.68479 | 5.8241 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 221.2 | | | | | | | | | | KernelScale: 0.83721 | | 255 | 6 | Accept | 0.12142 | 2.4508 | 0.0038305 | 271 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.99817 | | | | | | | | | | KernelScale: 218.44 | | 256 | 6 | Accept | 0.74165 | 9.4873 | 0.0038305 | 271 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.040486 | | | | | | | | | | KernelScale: 0.29035 | | 257 | 6 | Accept | 0.043982 | 0.79279 | 0.0038305 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 258 | 6 | Accept | 0.02506 | 23.587 | 0.0038305 | 1084 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 8.9184e-06 | | | | | | | | | | LayerSizes: [ 12 173 ] | | 259 | 6 | Accept | 0.073103 | 5.3417 | 0.0038305 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 1.1764e-05 | | | | | | | | | | LayerSizes: [ 4 2 61 ] | | 260 | 6 | Accept | 0.74165 | 9.3574 | 0.0038305 | 271 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 244 | | | | | | | | | | MinLeafSize: 888 | | | | | | | | | | MaxNumSplits: 43 | |====================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Training set | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | size | | | |====================================================================================================================================================| | 261 | 6 | Accept | 0.64155 | 3.5717 | 0.0038305 | 271 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 5.9957e-06 | | | | | | | | | | LayerSizes: [ 36 12 ] | | 262 | 6 | Accept | 0.056166 | 0.71336 | 0.0038305 | 271 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 263 | 6 | Accept | 0.052012 | 0.73278 | 0.0038305 | 1084 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 264 | 6 | Accept | 0.19305 | 2.7618 | 0.0038305 | 271 | knn | NumNeighbors: 80 | | 265 | 6 | Accept | 0.047351 | 8.4373 | 0.0038305 | 271 | net | Activations: sigmoid | | | | | | | | | | Standardize: fa...
__________________________________________________________ Optimization completed. Total iterations: 595 Total elapsed time: 1885.9532 seconds Total time for training and validation: 10791.4551 seconds Best observed learner is an ensemble model with: Learner: ensemble Method: AdaBoostM2 NumLearningCycles: 223 MinLeafSize: 1 MaxNumSplits: 75 Observed validation loss: 0.0038305 Time for training and validation: 92.5414 seconds Documentation for fitcauto display
fitcauto によって返される最終的なモデルが、観測された最適な学習器となります。モデルを返す前に、関数はすべての学習データ (XTrain と YTrain)、リストされている Learner (またはモデル) のタイプ、および表示されたハイパーパラメーター値を使用して、モデルの再学習を行います。
テスト セットのパフォーマンスの評価
テスト データ セットに対する最終モデルのパフォーマンスを評価します。
testAccuracy = 1 - loss(Mdl,XTest,YTest)
testAccuracy = 0.9958
最終モデルは、99% を超える観測値を正しく分類しています。
特徴選択と分類器自動選択の組み合わせ
fitcauto を使用し、table で指定した予測子データと応答データに基づいて、最適化されたハイパーパラメーターをもつ分類モデルを自動的に選択します。データを fitcauto に渡す前に特徴選択を実行して、重要でない予測子をデータ セットから削除します。
データの読み込みと分割
標本ファイル CreditRating_Historical.dat を table に読み取ります。予測子データは、法人顧客リストの財務比率と業種の情報で構成されます。応答変数は、格付機関が割り当てた格付けから構成されます。データ セットの最初の数行をプレビューします。
creditrating = readtable("CreditRating_Historical.dat");
head(creditrating) ID WC_TA RE_TA EBIT_TA MVE_BVTD S_TA Industry Rating
_____ ______ ______ _______ ________ _____ ________ _______
62394 0.013 0.104 0.036 0.447 0.142 3 {'BB' }
48608 0.232 0.335 0.062 1.969 0.281 8 {'A' }
42444 0.311 0.367 0.074 1.935 0.366 1 {'A' }
48631 0.194 0.263 0.062 1.017 0.228 4 {'BBB'}
43768 0.121 0.413 0.057 3.647 0.466 12 {'AAA'}
39255 -0.117 -0.799 0.01 0.179 0.082 4 {'CCC'}
62236 0.087 0.158 0.049 0.816 0.324 2 {'BBB'}
39354 0.005 0.181 0.034 2.597 0.388 7 {'AA' }
変数 ID の各値は一意の顧客 ID であるため (つまり、length(unique(creditrating.ID)) は creditrating に含まれる観測値の数に等しい)、変数 ID は予測子としては適切ではありません。変数 ID を table から削除し、変数 Industry を categorical 変数に変換します。
creditrating = removevars(creditrating,"ID");
creditrating.Industry = categorical(creditrating.Industry);データを学習セットとテスト セットに分割します。モデル選択とハイパーパラメーター調整のプロセスに観測値の約 85% を使用し、fitcauto によって返された、新しいデータに対する最終モデルのパフォーマンスのテストに観測値の 15% を使用します。cvpartition を使用してデータを分割します。
rng("default") % For reproducibility of the partition c = cvpartition(creditrating.Rating,"Holdout",0.15); trainingIndices = training(c); % Indices for the training set testIndices = test(c); % Indices for the test set creditTrain = creditrating(trainingIndices,:); creditTest = creditrating(testIndices,:);
特徴選択の実行
学習データを fitcauto に渡す前に、関数 fscchi2 を使用して重要な予測子を見つけます。関数 bar を使用して、予測子スコアを可視化します。Inf となるスコアがあっても、bar は Inf 値を破棄するため、最初に有限のスコアをプロットしてから、Inf スコアを有限値として別の色でプロットします。
[idx,scores] = fscchi2(creditTrain,"Rating"); bar(scores(idx)) % Represents finite scores hold on veryImportant = isinf(scores); finiteMax = max(scores(~veryImportant)); bar(finiteMax*veryImportant(idx)) % Represents Inf scores hold off xticklabels(strrep(creditTrain.Properties.VariableNames(idx),"_","\_")) xtickangle(45) legend(["Finite Scores","Inf Scores"])
予測子 Industry のスコアは低く、0.05 より大きい p 値に相当します。これは、Industry が重要な特徴ではない可能性があることを示しています。学習データ セットとテスト データ セットから、特徴量 Industry を削除します。
creditTrain = removevars(creditTrain,'Industry'); creditTest = removevars(creditTest,'Industry');
fitcauto の実行
学習データを fitcauto に渡します。この関数は、ベイズ最適化を使用してモデルとそのハイパーパラメーター値を選択し、パフォーマンスが最大となることが期待される学習済みモデル Mdl を返します。使用可能なすべての学習器のタイプを試すよう指定し、最適化を並列実行するよう指定します (Parallel Computing Toolbox™ が必要)。ベイズ最適化の詳細が格納された 2 番目の出力 Results を返します。
このプロセスにいくらか時間がかかることを見込んでください。既定の設定では、fitcauto は、最適化のプロット、および最適化の結果の反復表示を提供します。これらの結果を解釈する方法の詳細については、Verbose の表示を参照してください。
options = struct("UseParallel",true); [Mdl,Results] = fitcauto(creditTrain,"Rating", ... "Learners","all","HyperparameterOptimizationOptions",options);
Starting parallel pool (parpool) using the 'Processes' profile ... 19-Sep-2023 11:47:29: Job Running. Waiting for parallel pool workers to connect ... Connected to parallel pool with 6 workers. Copying objective function to workers... Done copying objective function to workers. Learner types to explore: discr, ensemble, kernel, knn, linear, nb, net, svm, tree Total iterations (MaxObjectiveEvaluations): 270 Total time (MaxTime): Inf |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 1 | 6 | Best | 0.42806 | 5.6782 | 0.42806 | 0.42806 | discr | Delta: 1.1034e-06 | | | | | | | | | | Gamma: 0.13756 | | 2 | 4 | Accept | 0.6904 | 11.96 | 0.32306 | 0.32306 | knn | NumNeighbors: 192 | | | | | | | | | | Distance: jaccard | | | | | | | | | | Standardize: true | | 3 | 4 | Accept | 0.6548 | 6.132 | 0.32306 | 0.32306 | knn | NumNeighbors: 55 | | | | | | | | | | Distance: jaccard | | | | | | | | | | Standardize: true | | 4 | 4 | Best | 0.32306 | 5.7472 | 0.32306 | 0.32306 | tree | MinLeafSize: 2 | | 5 | 3 | Accept | 0.54442 | 7.5152 | 0.32306 | 0.32306 | knn | NumNeighbors: 457 | | | | | | | | | | Distance: mahalanobis | | | | | | | | | | Standardize: false | | 6 | 3 | Accept | 0.38917 | 0.63675 | 0.32306 | 0.32306 | knn | NumNeighbors: 1 | | | | | | | | | | Distance: chebychev | | | | | | | | | | Standardize: true | | 7 | 6 | Accept | 0.32306 | 1.0047 | 0.32306 | 0.32306 | tree | MinLeafSize: 2 | | 8 | 6 | Accept | 0.6548 | 2.3049 | 0.32306 | 0.32306 | knn | NumNeighbors: 128 | | | | | | | | | | Distance: spearman | | | | | | | | | | Standardize: false | | 9 | 6 | Accept | 0.74185 | 4.6804 | 0.32306 | 0.32306 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.030894 | | | | | | | | | | LayerSizes: [ 233 3 ] | | 10 | 6 | Accept | 0.73826 | 6.0779 | 0.32306 | 0.32306 | nb | DistributionNames: kernel | | | | | | | | | | Width: 12.992 | | | | | | | | | | Standardize: false | | 11 | 6 | Accept | 0.7245 | 6.0896 | 0.32306 | 0.32306 | nb | DistributionNames: kernel | | | | | | | | | | Width: 8.005 | | | | | | | | | | Standardize: false | | 12 | 6 | Accept | 0.55669 | 1.8373 | 0.32306 | 0.32306 | knn | NumNeighbors: 704 | | | | | | | | | | Distance: correlation | | | | | | | | | | Standardize: false | | 13 | 6 | Best | 0.29106 | 5.3258 | 0.29106 | 0.29106 | linear | Coding: onevsone | | | | | | | | | | Lambda: 0.02725 | | | | | | | | | | Learner: svm | | 14 | 6 | Accept | 0.3796 | 1.6773 | 0.29106 | 0.29106 | knn | NumNeighbors: 10 | | | | | | | | | | Distance: mahalanobis | | | | | | | | | | Standardize: false | | 15 | 6 | Best | 0.29076 | 25.701 | 0.29076 | 0.29076 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 416 | | | | | | | | | | LearnRate: 0.012912 | | | | | | | | | | MinLeafSize: 306 | | 16 | 6 | Accept | 0.77176 | 21.367 | 0.29076 | 0.29076 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 0.0038019 | | | | | | | | | | Lambda: 1.7178e-06 | | | | | | | | | | Standardize: true | | 17 | 6 | Accept | 0.74035 | 7.1263 | 0.29076 | 0.29076 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 10.765 | | | | | | | | | | Lambda: 0.11328 | | | | | | | | | | Standardize: false | | 18 | 6 | Best | 0.26802 | 11.788 | 0.26802 | 0.29076 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 0.51078 | | | | | | | | | | Lambda: 0.0059423 | | | | | | | | | | Standardize: false | | 19 | 5 | Accept | 0.28059 | 1.1595 | 0.26802 | 0.29076 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 20 | 5 | Accept | 0.60425 | 0.67837 | 0.26802 | 0.29076 | discr | Delta: 1.9023 | | | | | | | | | | Gamma: 0.10664 | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 21 | 5 | Accept | 0.43015 | 0.69613 | 0.26802 | 0.29076 | discr | Delta: 4.8522e-06 | | | | | | | | | | Gamma: 0.70512 | | 22 | 5 | Accept | 0.56775 | 0.10142 | 0.26802 | 0.29076 | discr | Delta: 1.3809 | | | | | | | | | | Gamma: 0.41668 | | 23 | 6 | Accept | 0.43195 | 0.16103 | 0.26802 | 0.29076 | discr | Delta: 0.0004076 | | | | | | | | | | Gamma: 0.6689 | | 24 | 6 | Accept | 0.43195 | 0.11128 | 0.26802 | 0.29076 | discr | Delta: 0.0004076 | | | | | | | | | | Gamma: 0.6689 | | 25 | 6 | Accept | 0.4125 | 0.27417 | 0.26802 | 0.29076 | knn | NumNeighbors: 1 | | | | | | | | | | Distance: cosine | | | | | | | | | | Standardize: true | | 26 | 6 | Accept | 0.29584 | 7.3947 | 0.26802 | 0.29076 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 13.555 | | | | | | | | | | Lambda: 2.3981e-06 | | | | | | | | | | Standardize: false | | 27 | 6 | Accept | 0.47652 | 3.5675 | 0.26802 | 0.29076 | linear | Coding: onevsall | | | | | | | | | | Lambda: 4.1565e-09 | | | | | | | | | | Learner: svm | | 28 | 6 | Accept | 0.32306 | 1.2457 | 0.26802 | 0.29076 | tree | MinLeafSize: 2 | | 29 | 6 | Accept | 0.29614 | 3.3084 | 0.26802 | 0.29383 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 26 | | | | | | | | | | LearnRate: 0.0039975 | | | | | | | | | | MinLeafSize: 16 | | 30 | 6 | Accept | 0.74185 | 4.0467 | 0.26802 | 0.29383 | nb | DistributionNames: kernel | | | | | | | | | | Width: 39.895 | | | | | | | | | | Standardize: true | | 31 | 6 | Accept | 0.44481 | 0.10137 | 0.26802 | 0.29383 | discr | Delta: 0.36342 | | | | | | | | | | Gamma: 0.1396 | | 32 | 6 | Best | 0.26174 | 0.81732 | 0.26174 | 0.28329 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 12 | | | | | | | | | | LearnRate: 0.3237 | | | | | | | | | | MinLeafSize: 5 | | 33 | 6 | Accept | 0.49985 | 2.9761 | 0.26174 | 0.28329 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.0010113 | | | | | | | | | | KernelScale: 0.59363 | | | | | | | | | | Standardize: false | | 34 | 6 | Accept | 0.29734 | 0.26532 | 0.26174 | 0.28329 | tree | MinLeafSize: 9 | | 35 | 6 | Accept | 0.67664 | 3.4061 | 0.26174 | 0.28329 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 216.83 | | | | | | | | | | Lambda: 0.00011265 | | | | | | | | | | Standardize: false | | 36 | 6 | Accept | 0.26354 | 2.2828 | 0.26174 | 0.28329 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.042439 | | | | | | | | | | Standardize: false | | 37 | 6 | Best | 0.25426 | 39.685 | 0.25426 | 0.28329 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.257e-08 | | | | | | | | | | LayerSizes: [ 37 5 ] | | 38 | 6 | Accept | 0.44331 | 3.6915 | 0.25426 | 0.31805 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 53 | | | | | | | | | | LearnRate: NaN | | | | | | | | | | MinLeafSize: 581 | | 39 | 6 | Accept | 0.58959 | 1.3275 | 0.25426 | 0.31805 | knn | NumNeighbors: 1268 | | | | | | | | | | Distance: euclidean | | | | | | | | | | Standardize: true | | 40 | 6 | Accept | 0.60245 | 1.2026 | 0.25426 | 0.31805 | knn | NumNeighbors: 1496 | | | | | | | | | | Distance: chebychev | | | | | | | | | | Standardize: false | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 41 | 6 | Accept | 0.48011 | 1.4678 | 0.25426 | 0.31805 | linear | Coding: onevsall | | | | | | | | | | Lambda: 6.1865e-09 | | | | | | | | | | Learner: svm | | 42 | 6 | Accept | 0.28059 | 0.18379 | 0.25426 | 0.31805 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 43 | 6 | Accept | 0.42866 | 0.14447 | 0.25426 | 0.31805 | discr | Delta: 2.1405e-05 | | | | | | | | | | Gamma: 0.48046 | | 44 | 6 | Accept | 0.74185 | 2.8947 | 0.25426 | 0.31805 | nb | DistributionNames: kernel | | | | | | | | | | Width: 20.362 | | | | | | | | | | Standardize: true | | 45 | 6 | Accept | 0.29285 | 1.7638 | 0.25426 | 0.31805 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 1.9198 | | | | | | | | | | KernelScale: 14.017 | | | | | | | | | | Standardize: true | | 46 | 6 | Accept | 0.74185 | 1.8807 | 0.25426 | 0.31805 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.019959 | | | | | | | | | | KernelScale: 699 | | | | | | | | | | Standardize: false | | 47 | 6 | Accept | 0.74185 | 2.7402 | 0.25426 | 0.31805 | nb | DistributionNames: kernel | | | | | | | | | | Width: 74.252 | | | | | | | | | | Standardize: false | | 48 | 6 | Best | 0.25277 | 173.28 | 0.25277 | 0.31805 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 7.4214e-07 | | | | | | | | | | LayerSizes: [ 50 186 ] | | 49 | 6 | Accept | 0.74185 | 0.9834 | 0.25277 | 0.31805 | discr | Delta: 598.21 | | | | | | | | | | Gamma: 0.35874 | | 50 | 6 | Accept | 0.30242 | 0.5476 | 0.25277 | 0.3135 | tree | MinLeafSize: 217 | | 51 | 6 | Accept | 0.46485 | 0.10709 | 0.25277 | 0.32388 | tree | MinLeafSize: 646 | | 52 | 6 | Accept | 0.25426 | 6.2573 | 0.25277 | 0.31621 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 58 | | | | | | | | | | LearnRate: NaN | | | | | | | | | | MinLeafSize: 54 | | 53 | 6 | Best | 0.2423 | 4.028 | 0.2423 | 0.31621 | linear | Coding: onevsone | | | | | | | | | | Lambda: 4.6366e-07 | | | | | | | | | | Learner: svm | | 54 | 6 | Accept | 0.28238 | 190.7 | 0.2423 | 0.31621 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.8922e-08 | | | | | | | | | | LayerSizes: [ 57 138 4 ] | | 55 | 6 | Accept | 0.47113 | 0.78798 | 0.2423 | 0.31621 | linear | Coding: onevsall | | | | | | | | | | Lambda: 0.43895 | | | | | | | | | | Learner: svm | | 56 | 6 | Accept | 0.74185 | 2.457 | 0.2423 | 0.31621 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 1.2443 | | | | | | | | | | KernelScale: 574.46 | | | | | | | | | | Standardize: false | | 57 | 6 | Accept | 0.27131 | 7.5522 | 0.2423 | 0.29147 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 104 | | | | | | | | | | LearnRate: 0.015591 | | | | | | | | | | MinLeafSize: 82 | | 58 | 6 | Accept | 0.73617 | 8.6607 | 0.2423 | 0.29147 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 23.192 | | | | | | | | | | Lambda: 0.014674 | | | | | | | | | | Standardize: true | | 59 | 6 | Accept | 0.60126 | 1.693 | 0.2423 | 0.29147 | linear | Coding: onevsone | | | | | | | | | | Lambda: 0.57404 | | | | | | | | | | Learner: svm | | 60 | 6 | Accept | 0.344 | 0.35302 | 0.2423 | 0.29147 | knn | NumNeighbors: 16 | | | | | | | | | | Distance: cosine | | | | | | | | | | Standardize: true | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 61 | 6 | Accept | 0.38379 | 11.443 | 0.2423 | 0.29147 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 8.6444 | | | | | | | | | | Lambda: 0.0027745 | | | | | | | | | | Standardize: false | | 62 | 6 | Accept | 0.47442 | 177.71 | 0.2423 | 0.29147 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.0095264 | | | | | | | | | | KernelScale: 0.0085326 | | | | | | | | | | Standardize: true | | 63 | 6 | Accept | 0.61113 | 0.57662 | 0.2423 | 0.29147 | tree | MinLeafSize: 926 | | 64 | 6 | Accept | 0.28059 | 0.69666 | 0.2423 | 0.29147 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 65 | 6 | Accept | 0.27401 | 0.26895 | 0.2423 | 0.29147 | tree | MinLeafSize: 16 | | 66 | 6 | Accept | 0.30182 | 0.11504 | 0.2423 | 0.29147 | tree | MinLeafSize: 227 | | 67 | 6 | Accept | 0.74185 | 0.73959 | 0.2423 | 0.29147 | discr | Delta: 851.21 | | | | | | | | | | Gamma: 0.66152 | | 68 | 6 | Best | 0.2402 | 16.647 | 0.2402 | 0.29147 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 1.692e-06 | | | | | | | | | | LayerSizes: 2 | | 69 | 6 | Accept | 0.25277 | 12.732 | 0.2402 | 0.29147 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 4.1744 | | | | | | | | | | Lambda: 5.6663e-06 | | | | | | | | | | Standardize: true | | 70 | 6 | Accept | 0.47771 | 4.5034 | 0.2402 | 0.29147 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 67.044 | | | | | | | | | | Lambda: 3.4123e-05 | | | | | | | | | | Standardize: true | | 71 | 6 | Accept | 0.43314 | 0.11809 | 0.2402 | 0.29147 | discr | Delta: 1.6835e-06 | | | | | | | | | | Gamma: 0.54078 | | 72 | 6 | Accept | 0.6219 | 4.101 | 0.2402 | 0.29147 | nb | DistributionNames: kernel | | | | | | | | | | Width: 1.978 | | | | | | | | | | Standardize: false | | 73 | 6 | Accept | 0.38109 | 1.5955 | 0.2402 | 0.29147 | knn | NumNeighbors: 9 | | | | | | | | | | Distance: mahalanobis | | | | | | | | | | Standardize: false | | 74 | 6 | Accept | 0.27281 | 8.9571 | 0.2402 | 0.27844 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 174 | | | | | | | | | | LearnRate: 0.0060499 | | | | | | | | | | MinLeafSize: 71 | | 75 | 6 | Accept | 0.26443 | 448.01 | 0.2402 | 0.27844 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 1.9372 | | | | | | | | | | KernelScale: 0.020055 | | | | | | | | | | Standardize: true | | 76 | 6 | Accept | 0.74185 | 2.6428 | 0.2402 | 0.27844 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.042444 | | | | | | | | | | LayerSizes: [ 63 16 59 ] | | 77 | 6 | Accept | 0.24828 | 8.5545 | 0.2402 | 0.27844 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 7.1139 | | | | | | | | | | Lambda: 4.2402e-07 | | | | | | | | | | Standardize: false | | 78 | 6 | Accept | 0.3778 | 1.7431 | 0.2402 | 0.27844 | linear | Coding: onevsone | | | | | | | | | | Lambda: 0.094492 | | | | | | | | | | Learner: logistic | | 79 | 6 | Accept | 0.28059 | 0.28729 | 0.2402 | 0.27844 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 80 | 6 | Accept | 0.48938 | 1.0166 | 0.2402 | 0.27844 | linear | Coding: onevsall | | | | | | | | | | Lambda: 1.2191e-08 | | | | | | | | | | Learner: svm | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 81 | 6 | Accept | 0.30272 | 549.27 | 0.2402 | 0.27844 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 2.2033e-07 | | | | | | | | | | LayerSizes: [ 289 226 ] | | 82 | 6 | Accept | 0.73078 | 1.4068 | 0.2402 | 0.27844 | linear | Coding: onevsone | | | | | | | | | | Lambda: 18.548 | | | | | | | | | | Learner: svm | | 83 | 6 | Accept | 0.28747 | 517.33 | 0.2402 | 0.27844 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 0.70629 | | | | | | | | | | KernelScale: 0.0071032 | | | | | | | | | | Standardize: true | | 84 | 6 | Accept | 0.28059 | 0.74081 | 0.2402 | 0.27844 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 85 | 6 | Accept | 0.28507 | 5.9221 | 0.2402 | 0.27605 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 77 | | | | | | | | | | LearnRate: 0.47485 | | | | | | | | | | MinLeafSize: 343 | | 86 | 6 | Accept | 0.24798 | 16.845 | 0.2402 | 0.2612 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 7.0935e-07 | | | | | | | | | | LayerSizes: 7 | | 87 | 6 | Accept | 0.43673 | 0.41615 | 0.2402 | 0.2612 | knn | NumNeighbors: 5 | | | | | | | | | | Distance: cosine | | | | | | | | | | Standardize: false | | 88 | 6 | Accept | 0.28717 | 102.99 | 0.2402 | 0.27151 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.5286e-08 | | | | | | | | | | LayerSizes: [ 154 2 129 ] | | 89 | 6 | Accept | 0.49237 | 0.10707 | 0.2402 | 0.27151 | discr | Delta: 0.64058 | | | | | | | | | | Gamma: 0.66954 | | 90 | 6 | Accept | 0.35597 | 3.3207 | 0.2402 | 0.27151 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 1.68 | | | | | | | | | | Lambda: 0.001185 | | | | | | | | | | Standardize: true | | 91 | 6 | Accept | 0.28059 | 0.1242 | 0.2402 | 0.27151 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 92 | 6 | Accept | 0.42746 | 0.086665 | 0.2402 | 0.27151 | discr | Delta: 0.0009318 | | | | | | | | | | Gamma: 0.92633 | | 93 | 6 | Accept | 0.3778 | 1.5777 | 0.2402 | 0.27151 | linear | Coding: onevsall | | | | | | | | | | Lambda: 3.2058e-06 | | | | | | | | | | Learner: logistic | | 94 | 6 | Accept | 0.49835 | 603.65 | 0.2402 | 0.27151 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 472.88 | | | | | | | | | | KernelScale: 0.0042756 | | | | | | | | | | Standardize: false | | 95 | 6 | Accept | 0.27101 | 0.19458 | 0.2402 | 0.27151 | tree | MinLeafSize: 19 | | 96 | 6 | Accept | 0.43165 | 0.15957 | 0.2402 | 0.27151 | discr | Delta: 7.5638e-06 | | | | | | | | | | Gamma: 0.68017 | | 97 | 6 | Accept | 0.31469 | 0.31516 | 0.2402 | 0.27151 | knn | NumNeighbors: 17 | | | | | | | | | | Distance: seuclidean | | | | | | | | | | Standardize: false | | 98 | 5 | Accept | 0.24409 | 72.736 | 0.2402 | 0.2628 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.0826e-07 | | | | | | | | | | LayerSizes: [ 67 4 ] | | 99 | 5 | Accept | 0.24349 | 37.128 | 0.2402 | 0.2628 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.918e-05 | | | | | | | | | | LayerSizes: [ 1 28 ] | | 100 | 6 | Accept | 0.67275 | 1.0718 | 0.2402 | 0.2628 | linear | Coding: onevsall | | | | | | | | | | Lambda: 2.2997 | | | | | | | | | | Learner: logistic | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 101 | 6 | Accept | 0.67275 | 0.93641 | 0.2402 | 0.2628 | linear | Coding: onevsall | | | | | | | | | | Lambda: 2.2997 | | | | | | | | | | Learner: logistic | | 102 | 6 | Accept | 0.70087 | 0.62985 | 0.2402 | 0.2628 | knn | NumNeighbors: 1 | | | | | | | | | | Distance: spearman | | | | | | | | | | Standardize: false | | 103 | 6 | Accept | 0.75441 | 7.2731 | 0.2402 | 0.2628 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 0.05141 | | | | | | | | | | Lambda: 0.00026262 | | | | | | | | | | Standardize: true | | 104 | 6 | Accept | 0.46784 | 2.6259 | 0.2402 | 0.2628 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 709.45 | | | | | | | | | | KernelScale: 110.07 | | | | | | | | | | Standardize: true | | 105 | 6 | Accept | 0.55609 | 2.4477 | 0.2402 | 0.2628 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 0.98101 | | | | | | | | | | KernelScale: 338.53 | | | | | | | | | | Standardize: true | | 106 | 5 | Accept | 0.30182 | 8.9363 | 0.2402 | 0.2628 | ensemble | Method: RUSBoost | | | | | | | | | | NumLearningCycles: 108 | | | | | | | | | | LearnRate: 0.091127 | | | | | | | | | | MinLeafSize: 93 | | 107 | 5 | Accept | 0.42626 | 0.1085 | 0.2402 | 0.2628 | discr | Delta: 0.063725 | | | | | | | | | | Gamma: 0.26362 | | 108 | 5 | Accept | 0.37751 | 1.6217 | 0.2402 | 0.2628 | linear | Coding: onevsall | | | | | | | | | | Lambda: 3.616e-07 | | | | | | | | | | Learner: logistic | | 109 | 5 | Accept | 0.74185 | 0.19511 | 0.2402 | 0.2628 | tree | MinLeafSize: 1547 | | 110 | 5 | Accept | 0.48639 | 0.085107 | 0.2402 | 0.2628 | tree | MinLeafSize: 838 | | 111 | 6 | Accept | 0.28059 | 0.21159 | 0.2402 | 0.2628 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 112 | 6 | Accept | 0.28059 | 0.65962 | 0.2402 | 0.2628 | nb | DistributionNames: normal | | | | | | | | | | Width: NaN | | | | | | | | | | Standardize: - | | 113 | 6 | Accept | 0.26683 | 0.23129 | 0.2402 | 0.2628 | tree | MinLeafSize: 57 | | 114 | 6 | Accept | 0.29704 | 0.32876 | 0.2402 | 0.2628 | knn | NumNeighbors: 4 | | | | | | | | | | Distance: cityblock | | | | | | | | | | Standardize: false | | 115 | 6 | Accept | 0.30302 | 1.5298 | 0.2402 | 0.2628 | svm | Coding: onevsone | | | | | | | | | | BoxConstraint: 202.17 | | | | | | | | | | KernelScale: 101.19 | | | | | | | | | | Standardize: false | | 116 | 6 | Accept | 0.2411 | 5.3518 | 0.2402 | 0.2492 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0013411 | | | | | | | | | | LayerSizes: [ 44 6 2 ] | | 117 | 6 | Accept | 0.3437 | 1.3283 | 0.2402 | 0.2492 | nb | DistributionNames: kernel | | | | | | | | | | Width: 0.0048194 | | | | | | | | | | Standardize: true | | 118 | 6 | Accept | 0.28597 | 12.501 | 0.2402 | 0.2492 | ensemble | Method: RUSBoost | | | | | | | | | | NumLearningCycles: 154 | | | | | | | | | | LearnRate: 0.083217 | | | | | | | | | | MinLeafSize: 2 | | 119 | 6 | Accept | 0.3802 | 12.007 | 0.2402 | 0.2492 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 203 | | | | | | | | | | LearnRate: NaN | | | | | | | | | | MinLeafSize: 544 | | 120 | 6 | Accept | 0.24858 | 31.641 | 0.2402 | 0.24914 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 3.3971e-06 | | | | | | | | | | LayerSizes: 36 | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 121 | 6 | Accept | 0.27789 | 62.185 | 0.2402 | 0.24793 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.2607e-06 | | | | | | | | | | LayerSizes: [ 62 21 ] | | 122 | 6 | Accept | 0.79599 | 4.705 | 0.2402 | 0.24793 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 0.0011217 | | | | | | | | | | Lambda: 1.0606e-05 | | | | | | | | | | Standardize: true | | 123 | 6 | Accept | 0.3781 | 1.6477 | 0.2402 | 0.24793 | linear | Coding: onevsall | | | | | | | | | | Lambda: 5.2732e-06 | | | | | | | | | | Learner: logistic | | 124 | 6 | Accept | 0.30302 | 0.17372 | 0.2402 | 0.24793 | tree | MinLeafSize: 188 | | 125 | 6 | Accept | 0.42238 | 0.1337 | 0.2402 | 0.24793 | discr | Delta: 2.4829e-05 | | | | | | | | | | Gamma: 0.029235 | | 126 | 6 | Accept | 0.3087 | 9.5549 | 0.2402 | 0.24793 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 6.788 | | | | | | | | | | Lambda: 7.0582e-06 | | | | | | | | | | Standardize: true | | 127 | 6 | Accept | 0.25965 | 2.4983 | 0.2402 | 0.24793 | ensemble | Method: AdaBoostM2 | | | | | | | | | | NumLearningCycles: 33 | | | | | | | | | | LearnRate: 0.61112 | | | | | | | | | | MinLeafSize: 1 | | 128 | 6 | Accept | 0.74394 | 2.8462 | 0.2402 | 0.24793 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 0.0031986 | | | | | | | | | | Lambda: 0.0061281 | | | | | | | | | | Standardize: true | | 129 | 6 | Accept | 0.71373 | 1.5234 | 0.2402 | 0.24793 | linear | Coding: onevsone | | | | | | | | | | Lambda: 6.7051 | | | | | | | | | | Learner: svm | | 130 | 6 | Accept | 0.28118 | 6.9134 | 0.2402 | 0.24793 | ensemble | Method: Bag | | | | | | | | | | NumLearningCycles: 97 | | | | | | | | | | LearnRate: NaN | | | | | | | | | | MinLeafSize: 145 | | 131 | 6 | Accept | 0.2408 | 6.1538 | 0.2402 | 0.24814 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00088549 | | | | | | | | | | LayerSizes: [ 33 3 9 ] | | 132 | 6 | Accept | 0.2429 | 68.124 | 0.2402 | 0.24576 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.5221e-08 | | | | | | | | | | LayerSizes: [ 1 155 ] | | 133 | 6 | Accept | 0.31648 | 21.647 | 0.2402 | 0.24576 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 0.20239 | | | | | | | | | | Lambda: 4.5158e-07 | | | | | | | | | | Standardize: false | | 134 | 6 | Accept | 0.24319 | 13.099 | 0.2402 | 0.24536 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 6.6754e-05 | | | | | | | | | | LayerSizes: [ 21 2 12 ] | | 135 | 6 | Accept | 0.24349 | 42.136 | 0.2402 | 0.24452 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00090504 | | | | | | | | | | LayerSizes: [ 2 76 ] | | 136 | 6 | Accept | 0.24379 | 32.721 | 0.2402 | 0.24773 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 9.3254e-07 | | | | | | | | | | LayerSizes: [ 67 2 31 ] | | 137 | 6 | Accept | 0.37003 | 14.749 | 0.2402 | 0.24773 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 0.13081 | | | | | | | | | | Lambda: 5.3515e-07 | | | | | | | | | | Standardize: false | | 138 | 6 | Accept | 0.25725 | 3.9823 | 0.2402 | 0.24634 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00060459 | | | | | | | | | | LayerSizes: [ 7 11 1 ] | | 139 | 6 | Accept | 0.32336 | 1.576 | 0.2402 | 0.24899 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0026218 | | | | | | | | | | LayerSizes: [ 32 1 ] | | 140 | 6 | Accept | 0.2423 | 112.85 | 0.2402 | 0.24831 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00090124 | | | | | | | | | | LayerSizes: [ 45 235 ] | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 141 | 6 | Accept | 0.2426 | 4.0996 | 0.2402 | 0.24641 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.001478 | | | | | | | | | | LayerSizes: [ 2 5 7 ] | | 142 | 6 | Accept | 0.25845 | 8.462 | 0.2402 | 0.24641 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 9.6666 | | | | | | | | | | Lambda: 3.8579e-07 | | | | | | | | | | Standardize: false | | 143 | 6 | Accept | 0.24708 | 7.4252 | 0.2402 | 0.24641 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 12.213 | | | | | | | | | | Lambda: 3.1489e-07 | | | | | | | | | | Standardize: false | | 144 | 6 | Accept | 0.32366 | 80.46 | 0.2402 | 0.24672 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0059726 | | | | | | | | | | LayerSizes: [ 6 206 28 ] | | 145 | 6 | Accept | 0.24559 | 7.2735 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 23.752 | | | | | | | | | | Lambda: 4.133e-07 | | | | | | | | | | Standardize: false | | 146 | 6 | Accept | 0.551 | 829.22 | 0.2402 | 0.24672 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 35.361 | | | | | | | | | | KernelScale: 0.046602 | | | | | | | | | | Standardize: false | | 147 | 6 | Accept | 0.39306 | 5.8171 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 736.48 | | | | | | | | | | Lambda: 4.0716e-07 | | | | | | | | | | Standardize: false | | 148 | 5 | Accept | 0.28238 | 18.623 | 0.2402 | 0.24672 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 10.125 | | | | | | | | | | Lambda: 3.896e-07 | | | | | | | | | | Standardize: true | | 149 | 5 | Accept | 0.24828 | 10.748 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 30.83 | | | | | | | | | | Lambda: 3.8791e-07 | | | | | | | | | | Standardize: true | | 150 | 6 | Accept | 0.24978 | 8.8994 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 9.7302 | | | | | | | | | | Lambda: 1.3449e-05 | | | | | | | | | | Standardize: true | | 151 | 6 | Accept | 0.26264 | 8.6283 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 175.27 | | | | | | | | | | Lambda: 3.1699e-07 | | | | | | | | | | Standardize: true | | 152 | 6 | Accept | 0.34969 | 20.244 | 0.2402 | 0.24672 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 0.15104 | | | | | | | | | | Lambda: 3.2644e-07 | | | | | | | | | | Standardize: false | | 153 | 6 | Accept | 0.2429 | 6.7125 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 12.355 | | | | | | | | | | Lambda: 1.5584e-05 | | | | | | | | | | Standardize: false | | 154 | 6 | Accept | 0.24978 | 9.136 | 0.2402 | 0.24672 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 10.799 | | | | | | | | | | Lambda: 1.048e-05 | | | | | | | | | | Standardize: true | | 155 | 6 | Accept | 0.2414 | 8.568 | 0.2402 | 0.24376 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0016734 | | | | | | | | | | LayerSizes: [ 12 8 110 ] | | 156 | 6 | Accept | 0.27101 | 7.2439 | 0.2402 | 0.24376 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 44.514 | | | | | | | | | | Lambda: 1.6779e-05 | | | | | | | | | | Standardize: true | | 157 | 6 | Accept | 0.36584 | 7.3892 | 0.2402 | 0.24376 | kernel | Coding: onevsall | | | | | | | | | | KernelScale: 8.1563 | | | | | | | | | | Lambda: 2.0937e-05 | | | | | | | | | | Standardize: true | | 158 | 6 | Accept | 0.25067 | 8.8403 | 0.2402 | 0.24376 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 12.809 | | | | | | | | | | Lambda: 1.2454e-05 | | | | | | | | | | Standardize: true | | 159 | 6 | Accept | 0.65061 | 2.0949 | 0.2402 | 0.24279 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0019477 | | | | | | | | | | LayerSizes: [ 1 3 6 ] | | 160 | 6 | Accept | 0.25755 | 7.8532 | 0.2402 | 0.24279 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 14.631 | | | | | | | | | | Lambda: 2.5841e-05 | | | | | | | | | | Standardize: true | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 161 | 6 | Accept | 0.25037 | 6.1788 | 0.2402 | 0.24279 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 20.745 | | | | | | | | | | Lambda: 9.9875e-06 | | | | | | | | | | Standardize: false | | 162 | 6 | Accept | 0.2417 | 26.687 | 0.2402 | 0.24327 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018945 | | | | | | | | | | LayerSizes: [ 21 6 46 ] | | 163 | 6 | Accept | 0.25576 | 119.54 | 0.2402 | 0.24283 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0014331 | | | | | | | | | | LayerSizes: [ 14 248 ] | | 164 | 6 | Accept | 0.27371 | 8.5971 | 0.2402 | 0.24304 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0016931 | | | | | | | | | | LayerSizes: [ 8 8 ] | | 165 | 6 | Accept | 0.24708 | 25.212 | 0.2402 | 0.24265 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018028 | | | | | | | | | | LayerSizes: [ 4 23 15 ] | | 166 | 6 | Accept | 0.29494 | 3.5323 | 0.2402 | 0.24292 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018619 | | | | | | | | | | LayerSizes: 3 | | 167 | 6 | Accept | 0.25456 | 7.6825 | 0.2402 | 0.24292 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 12.099 | | | | | | | | | | Lambda: 2.8762e-05 | | | | | | | | | | Standardize: true | | 168 | 5 | Accept | 0.24349 | 18.661 | 0.2402 | 0.24344 | net | Activations: relu | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.001015 | | | | | | | | | | LayerSizes: [ 13 2 2 ] | | 169 | 5 | Accept | 0.30182 | 5.3939 | 0.2402 | 0.24344 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018397 | | | | | | | | | | LayerSizes: 9 | | 170 | 6 | Accept | 0.26324 | 7.3445 | 0.2402 | 0.24344 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 21.086 | | | | | | | | | | Lambda: 2.8333e-05 | | | | | | | | | | Standardize: true | | 171 | 6 | Accept | 0.74185 | 2.3678 | 0.2402 | 0.24227 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018972 | | | | | | | | | | LayerSizes: [ 1 86 3 ] | | 172 | 6 | Accept | 0.24678 | 5.8019 | 0.2402 | 0.24227 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 11.729 | | | | | | | | | | Lambda: 2.7926e-05 | | | | | | | | | | Standardize: false | | 173 | 6 | Accept | 0.28507 | 12.988 | 0.2402 | 0.2423 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0019114 | | | | | | | | | | LayerSizes: 64 | | 174 | 6 | Accept | 0.26922 | 5.6473 | 0.2402 | 0.2423 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 18.693 | | | | | | | | | | Lambda: 5.004e-05 | | | | | | | | | | Standardize: false | | 175 | 6 | Accept | 0.29285 | 24.595 | 0.2402 | 0.24255 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0018739 | | | | | | | | | | LayerSizes: [ 7 2 19 ] | | 176 | 6 | Accept | 0.277 | 12.779 | 0.2402 | 0.24253 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00088228 | | | | | | | | | | LayerSizes: [ 1 3 ] | | 177 | 6 | Accept | 0.28477 | 5.8382 | 0.2402 | 0.24253 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 19.288 | | | | | | | | | | Lambda: 7.3219e-05 | | | | | | | | | | Standardize: false | | 178 | 6 | Accept | 0.29465 | 5.7849 | 0.2402 | 0.24253 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 24.794 | | | | | | | | | | Lambda: 5.9159e-05 | | | | | | | | | | Standardize: false | | 179 | 6 | Accept | 0.26563 | 6.5897 | 0.2402 | 0.24253 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 11.818 | | | | | | | | | | Lambda: 0.00010735 | | | | | | | | | | Standardize: true | | 180 | 6 | Accept | 0.63895 | 14.083 | 0.2402 | 0.24457 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0018889 | | | | | | | | | | LayerSizes: [ 238 1 ] | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 181 | 6 | Accept | 0.24379 | 26.141 | 0.2402 | 0.24294 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 1.0457e-06 | | | | | | | | | | LayerSizes: [ 1 3 10 ] | | 182 | 6 | Accept | 0.26623 | 7.3764 | 0.2402 | 0.24294 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 14.976 | | | | | | | | | | Lambda: 9.3643e-05 | | | | | | | | | | Standardize: true | | 183 | 6 | Accept | 0.27251 | 7.5773 | 0.2402 | 0.24294 | kernel | Coding: onevsone | | | | | | | | | | KernelScale: 21.289 | | | | | | | | | | Lambda: 9.4769e-05 | | | | | | | | | | Standardize: true | | 184 | 6 | Accept | 0.4484 | 28.422 | 0.2402 | 0.24384 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0018927 | | | | | | | | | | LayerSizes: [ 7 102 ] | | 185 | 6 | Accept | 0.74185 | 3.078 | 0.2402 | 0.24566 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0012297 | | | | | | | | | | LayerSizes: [ 1 78 21 ] | | 186 | 6 | Accept | 0.242 | 71.324 | 0.2402 | 0.24343 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00010892 | | | | | | | | | | LayerSizes: [ 275 20 2 ] | | 187 | 6 | Accept | 0.24918 | 106.82 | 0.2402 | 0.24283 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 3.3853e-06 | | | | | | | | | | LayerSizes: [ 132 91 62 ] | | 188 | 6 | Accept | 0.42357 | 23.702 | 0.2402 | 0.24374 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0012734 | | | | | | | | | | LayerSizes: [ 7 22 1 ] | | 189 | 6 | Accept | 0.2423 | 14.378 | 0.2402 | 0.24278 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 1.2334e-05 | | | | | | | | | | LayerSizes: [ 1 35 2 ] | | 190 | 6 | Accept | 0.83398 | 1371.2 | 0.2402 | 0.24278 | svm | Coding: onevsall | | | | | | | | | | BoxConstraint: 293.96 | | | | | | | | | | KernelScale: 0.0027671 | | | | | | | | | | Standardize: false | | 191 | 6 | Accept | 0.2408 | 114.95 | 0.2402 | 0.24416 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00011921 | | | | | | | | | | LayerSizes: [ 17 11 155 ] | | 192 | 6 | Accept | 0.25905 | 142.69 | 0.2402 | 0.2422 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 4.4043e-07 | | | | | | | | | | LayerSizes: [ 191 4 8 ] | | 193 | 6 | Accept | 0.2402 | 29.568 | 0.2402 | 0.24339 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 3.1457e-05 | | | | | | | | | | LayerSizes: [ 1 205 ] | | 194 | 6 | Accept | 0.24319 | 23.318 | 0.2402 | 0.24389 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0012561 | | | | | | | | | | LayerSizes: [ 1 27 275 ] | | 195 | 6 | Accept | 0.74185 | 12.995 | 0.2402 | 0.24326 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00096808 | | | | | | | | | | LayerSizes: [ 2 138 167 ] | | 196 | 6 | Accept | 0.242 | 61.986 | 0.2402 | 0.24381 | net | Activations: relu | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 5.1918e-06 | | | | | | | | | | LayerSizes: [ 1 138 ] | | 197 | 6 | Accept | 0.2423 | 17.609 | 0.2402 | 0.24562 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 1.0751e-07 | | | | | | | | | | LayerSizes: [ 1 4 ] | | 198 | 6 | Accept | 0.24349 | 26.101 | 0.2402 | 0.24432 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.00012314 | | | | | | | | | | LayerSizes: [ 1 7 159 ] | | 199 | 6 | Accept | 0.26174 | 31.743 | 0.2402 | 0.24415 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0001629 | | | | | | | | | | LayerSizes: [ 1 17 17 ] | | 200 | 6 | Accept | 0.32605 | 73.406 | 0.2402 | 0.24432 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00054404 | | | | | | | | | | LayerSizes: [ 34 4 156 ] | |=======================================================================================================================================================| | Iter | Active | Eval | Validation | Time for training | Observed min | Estimated min | Learner | Hyperparameter: Value | | | workers | result | loss | & validation (sec)| validation loss | validation loss | | | |=======================================================================================================================================================| | 201 | 6 | Accept | 0.33413 | 4.3944 | 0.2402 | 0.2448 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00057617 | | | | | | | | | | LayerSizes: 7 | | 202 | 6 | Accept | 0.24469 | 3.371 | 0.2402 | 0.24631 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0015107 | | | | | | | | | | LayerSizes: [ 2 9 8 ] | | 203 | 6 | Accept | 0.32396 | 25.076 | 0.2402 | 0.24253 | net | Activations: sigmoid | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00083165 | | | | | | | | | | LayerSizes: [ 50 44 ] | | 204 | 6 | Accept | 0.24619 | 54.085 | 0.2402 | 0.24474 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.7518e-07 | | | | | | | | | | LayerSizes: [ 3 3 169 ] | | 205 | 6 | Accept | 0.2426 | 10.77 | 0.2402 | 0.24458 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0014455 | | | | | | | | | | LayerSizes: [ 2 114 3 ] | | 206 | 6 | Accept | 0.2405 | 31.434 | 0.2402 | 0.24382 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00020406 | | | | | | | | | | LayerSizes: [ 262 1 77 ] | | 207 | 6 | Accept | 0.2405 | 18.993 | 0.2402 | 0.24301 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00095774 | | | | | | | | | | LayerSizes: [ 5 193 19 ] | | 208 | 6 | Accept | 0.2411 | 11.172 | 0.2402 | 0.24492 | net | Activations: none | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.0012377 | | | | | | | | | | LayerSizes: [ 132 10 6 ] | | 209 | 6 | Accept | 0.2414 | 37.146 | 0.2402 | 0.24214 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0012408 | | | | | | | | | | LayerSizes: [ 2 149 197 ] | | 210 | 6 | Accept | 0.24678 | 97.751 | 0.2402 | 0.24251 | net | Activations: tanh | | | | | | | | | | Standardize: false | | | | | | | | | | Lambda: 0.00189 | | | | | | | | | | LayerSizes: [ 64 18 102 ] | | 211 | 6 | Accept | 0.26653 | 2.7798 | 0.2402 | 0.24229 | net | Activations: none | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 0.0016556 | | | | | | | | | | LayerSizes: [ 1 49 ] | | 212 | 6 | Accept | 0.2426 | 95.765 | 0.2402 | 0.24272 | net | Activations: sigmoid | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 2.4611e-05 | | | | | | | | | | LayerSizes: [ 3 120 34 ] | | 213 | 6 | Accept | 0.24738 | 33.035 | 0.2402 | 0.24206 | net | Activations: tanh | | | | | | | | | | Standardize: true | | | | | | | | | | Lambda: 7.6359e-05 | | | | | | | | | | LayerSizes: [ 1 25 ] | | 214 | 6 | Accept | 0.24798 | 231.65 | 0.2402 | 0.24358 | net | Activations: none | | | | | | ...
__________________________________________________________ Optimization completed. Total iterations: 270 Total elapsed time: 2468.5585 seconds Total time for training and validation: 12614.0749 seconds Best observed learner is a net model with: Learner: net Activations: relu Standardize: true Lambda: 1.692e-06 LayerSizes: 2 Observed validation loss: 0.2402 Time for training and validation: 16.6465 seconds Best estimated learner (returned model) is a net model with: Learner: net Activations: none Standardize: false Lambda: 0.00088549 LayerSizes: [33 3 9] Estimated validation loss: 0.24206 Estimated time for training and validation: 6.9666 seconds Documentation for fitcauto display
fitcauto によって返される最終的なモデルが、最適な推定学習器となります。モデルを返す前に、関数は学習データ全体 (creditTrain)、リストされている Learner (またはモデル) のタイプ、および表示されたハイパーパラメーター値を使用して、モデルの再学習を行います。
テスト セットのパフォーマンスの評価
モデル Mdl は、基準 "min-visited-mean" に従った、ベイズ最適化における最良の点に対応します。新しいデータに対するモデルのパフォーマンスを評価するには、モデルで観測された交差検証精度 (cvAccuracy)、およびベイズ最適化に基づき推定されたモデルの全体的なパフォーマンス (estimatedAccuracy) を確認します。
[x,~,iteration] = bestPoint(Results,"Criterion","min-visited-mean"); cvError = Results.ObjectiveTrace(iteration); cvAccuracy = 1 - cvError
cvAccuracy = 0.7592
estimatedError = predictObjective(Results,x); estimatedAccuracy = 1 - estimatedError
estimatedAccuracy = 0.7579
テスト セットに対するモデルのパフォーマンスを評価します。結果から混同行列を作成し、混同行列におけるクラスの順序を指定します。
testAccuracy = 1 - loss(Mdl,creditTest,"Rating")testAccuracy = 0.7471
cm = confusionchart(creditTest.Rating,predict(Mdl,creditTest)); sortClasses(cm,["AAA","AA","A","BBB","BB","B","CCC"])
入力引数
出力引数
詳細
ヒント
データ セットのサイズ、指定した学習器の数、および選択した最適化手法によっては、
fitcautoの処理に時間がかかる場合があります。Parallel Computing Toolbox のライセンスがある場合、最適化を並列実行して計算を高速化することができます。これを行うには、
"HyperparameterOptimizationOptions",struct("UseParallel",true)を指定します。この構造体に追加フィールドを含めて、その他の最適化の側面を制御できます。HyperparameterOptimizationOptionsを参照してください。学習セットの観測値の数が原因 (たとえば 10,000 を超える場合) でベイズ最適化による
fitcautoの実行に長い時間がかかる場合は、代わりに ASHA 最適化によるfitcautoを使用することを検討してください。データ セットの観測値が多いと、多くの場合、ベイズ最適化よりも ASHA 最適化の方が優れた解を速く見つけます。ASHA 最適化を使用するには、"HyperparameterOptimizationOptions",struct("Optimizer","asha")を指定します。この構造体に追加フィールドを含めて、その他の最適化の側面を制御できます。特に、時間の制約がある場合は、HyperparameterOptimizationOptions構造体のMaxTimeフィールドを指定して、fitcautoを実行する秒数を制限します。
アルゴリズム
代替機能
使用するデータ セットに最適なモデルがわからない場合は、分類学習器アプリを代わりに使用することができます。このアプリを使用すると、さまざまなモデルについてハイパーパラメーターを調整して、パフォーマンスが最も高い最適化済みモデルを選択できます。分類学習器では、モデルのハイパーパラメーターを調整する前に特定のモデルを選択しなければなりませんが、最適化可能なハイパーパラメーターの選択とハイパーパラメーター値の設定をより柔軟に行うことができます。ただし、このアプリでは、最適化を並列実行することや、観測値の重みを指定すること、事前確率を指定すること、ASHA 最適化を使用することはできません。詳細は、分類学習器アプリのハイパーパラメーターの最適化を参照してください。
使用するデータに適合するモデルがわかっている場合は、対応するモデル近似関数を使用し、名前と値の引数
OptimizeHyperparametersを指定して、ハイパーパラメーターを調整することもできます。複数のモデルの結果を比較して最適な分類器を選択できます。このプロセスの例については、ベイズ最適化を使用したモデル選択の自動化への移行を参照してください。
参照
[1] Li, Liam, Kevin Jamieson, Afshin Rostamizadeh, Ekaterina Gonina, Moritz Hardt, Benjamin Recht, and Ameet Talwalkar. “A System for Massively Parallel Hyperparameter Tuning.” ArXiv:1810.05934v5 [Cs], March 16, 2020. https://arxiv.org/abs/1810.05934v5.
拡張機能
バージョン履歴
R2020a で導入
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