分類学習機アプリで学習させた結果の出力方法

分類学習機アプリで5交差検証法を使って学習させた結果を一覧出力しようとしています．

混同行列やモデルの出力は出来たのですが，どのデータの予測が正解でどのデータの予測が誤りだったのか検証したいと考えています．

イメージとしては，以下の様になるのが理想です．

被験者ID　　分類ラベル　　予測結果

　　1　　　　Positive　　　Positive

　　2　　　　Positive　　　Negative

Answer 1

[Kojiro Saito]

モデルをエクスポートした後に元データと予測結果からtableを作ればできるかと思います。

ドキュメントの例に含まれているフィッシャーのアヤメデータを使ってサンプルを書きます。

t = readtable('fisheriris.csv');
% ID列を追加
t.ID = (1:height(t))';

% 分類学習器を起動
% classificationLearner
% 学習させたモデルを「コンパクトモデルのエクスポート」でcompactTrainedModelという変数でワークスペースで保存
% ここではmatファイルに出力したものを読み込みます
load compactTrainedModel

yPred = compactTrainedModel.predictFcn(t);

resultTable = table(t.ID, t.Species, yPred, 'VariableNames', {'ID', '分類ラベル', '予測結果'});
disp(resultTable)

    ID       分類ラベル          予測結果    
    ___    ______________    ______________

      1    {'setosa'    }    {'setosa'    }
      2    {'setosa'    }    {'setosa'    }
      3    {'setosa'    }    {'setosa'    }
      4    {'setosa'    }    {'setosa'    }
      5    {'setosa'    }    {'setosa'    }
      6    {'setosa'    }    {'setosa'    }
      7    {'setosa'    }    {'setosa'    }
      8    {'setosa'    }    {'setosa'    }
      9    {'setosa'    }    {'setosa'    }
     10    {'setosa'    }    {'setosa'    }
     11    {'setosa'    }    {'setosa'    }
     12    {'setosa'    }    {'setosa'    }
     13    {'setosa'    }    {'setosa'    }
     14    {'setosa'    }    {'setosa'    }
     15    {'setosa'    }    {'setosa'    }
     16    {'setosa'    }    {'setosa'    }
     17    {'setosa'    }    {'setosa'    }
     18    {'setosa'    }    {'setosa'    }
     19    {'setosa'    }    {'setosa'    }
     20    {'setosa'    }    {'setosa'    }
     21    {'setosa'    }    {'setosa'    }
     22    {'setosa'    }    {'setosa'    }
     23    {'setosa'    }    {'setosa'    }
     24    {'setosa'    }    {'setosa'    }
     25    {'setosa'    }    {'setosa'    }
     26    {'setosa'    }    {'setosa'    }
     27    {'setosa'    }    {'setosa'    }
     28    {'setosa'    }    {'setosa'    }
     29    {'setosa'    }    {'setosa'    }
     30    {'setosa'    }    {'setosa'    }
     31    {'setosa'    }    {'setosa'    }
     32    {'setosa'    }    {'setosa'    }
     33    {'setosa'    }    {'setosa'    }
     34    {'setosa'    }    {'setosa'    }
     35    {'setosa'    }    {'setosa'    }
     36    {'setosa'    }    {'setosa'    }
     37    {'setosa'    }    {'setosa'    }
     38    {'setosa'    }    {'setosa'    }
     39    {'setosa'    }    {'setosa'    }
     40    {'setosa'    }    {'setosa'    }
     41    {'setosa'    }    {'setosa'    }
     42    {'setosa'    }    {'setosa'    }
     43    {'setosa'    }    {'setosa'    }
     44    {'setosa'    }    {'setosa'    }
     45    {'setosa'    }    {'setosa'    }
     46    {'setosa'    }    {'setosa'    }
     47    {'setosa'    }    {'setosa'    }
     48    {'setosa'    }    {'setosa'    }
     49    {'setosa'    }    {'setosa'    }
     50    {'setosa'    }    {'setosa'    }
     51    {'versicolor'}    {'versicolor'}
     52    {'versicolor'}    {'versicolor'}
     53    {'versicolor'}    {'versicolor'}
     54    {'versicolor'}    {'versicolor'}
     55    {'versicolor'}    {'versicolor'}
     56    {'versicolor'}    {'versicolor'}
     57    {'versicolor'}    {'versicolor'}
     58    {'versicolor'}    {'versicolor'}
     59    {'versicolor'}    {'versicolor'}
     60    {'versicolor'}    {'versicolor'}
     61    {'versicolor'}    {'versicolor'}
     62    {'versicolor'}    {'versicolor'}
     63    {'versicolor'}    {'versicolor'}
     64    {'versicolor'}    {'versicolor'}
     65    {'versicolor'}    {'versicolor'}
     66    {'versicolor'}    {'versicolor'}
     67    {'versicolor'}    {'versicolor'}
     68    {'versicolor'}    {'versicolor'}
     69    {'versicolor'}    {'versicolor'}
     70    {'versicolor'}    {'versicolor'}
     71    {'versicolor'}    {'virginica' }
     72    {'versicolor'}    {'versicolor'}
     73    {'versicolor'}    {'versicolor'}
     74    {'versicolor'}    {'versicolor'}
     75    {'versicolor'}    {'versicolor'}
     76    {'versicolor'}    {'versicolor'}
     77    {'versicolor'}    {'versicolor'}
     78    {'versicolor'}    {'virginica' }
     79    {'versicolor'}    {'versicolor'}
     80    {'versicolor'}    {'versicolor'}
     81    {'versicolor'}    {'versicolor'}
     82    {'versicolor'}    {'versicolor'}
     83    {'versicolor'}    {'versicolor'}
     84    {'versicolor'}    {'virginica' }
     85    {'versicolor'}    {'versicolor'}
     86    {'versicolor'}    {'versicolor'}
     87    {'versicolor'}    {'versicolor'}
     88    {'versicolor'}    {'versicolor'}
     89    {'versicolor'}    {'versicolor'}
     90    {'versicolor'}    {'versicolor'}
     91    {'versicolor'}    {'versicolor'}
     92    {'versicolor'}    {'versicolor'}
     93    {'versicolor'}    {'versicolor'}
     94    {'versicolor'}    {'versicolor'}
     95    {'versicolor'}    {'versicolor'}
     96    {'versicolor'}    {'versicolor'}
     97    {'versicolor'}    {'versicolor'}
     98    {'versicolor'}    {'versicolor'}
     99    {'versicolor'}    {'versicolor'}
    100    {'versicolor'}    {'versicolor'}
    101    {'virginica' }    {'virginica' }
    102    {'virginica' }    {'virginica' }
    103    {'virginica' }    {'virginica' }
    104    {'virginica' }    {'virginica' }
    105    {'virginica' }    {'virginica' }
    106    {'virginica' }    {'virginica' }
    107    {'virginica' }    {'virginica' }
    108    {'virginica' }    {'virginica' }
    109    {'virginica' }    {'virginica' }
    110    {'virginica' }    {'virginica' }
    111    {'virginica' }    {'virginica' }
    112    {'virginica' }    {'virginica' }
    113    {'virginica' }    {'virginica' }
    114    {'virginica' }    {'virginica' }
    115    {'virginica' }    {'virginica' }
    116    {'virginica' }    {'virginica' }
    117    {'virginica' }    {'virginica' }
    118    {'virginica' }    {'virginica' }
    119    {'virginica' }    {'virginica' }
    120    {'virginica' }    {'virginica' }
    121    {'virginica' }    {'virginica' }
    122    {'virginica' }    {'virginica' }
    123    {'virginica' }    {'virginica' }
    124    {'virginica' }    {'virginica' }
    125    {'virginica' }    {'virginica' }
    126    {'virginica' }    {'virginica' }
    127    {'virginica' }    {'virginica' }
    128    {'virginica' }    {'virginica' }
    129    {'virginica' }    {'virginica' }
    130    {'virginica' }    {'virginica' }
    131    {'virginica' }    {'virginica' }
    132    {'virginica' }    {'virginica' }
    133    {'virginica' }    {'virginica' }
    134    {'virginica' }    {'virginica' }
    135    {'virginica' }    {'virginica' }
    136    {'virginica' }    {'virginica' }
    137    {'virginica' }    {'virginica' }
    138    {'virginica' }    {'virginica' }
    139    {'virginica' }    {'virginica' }
    140    {'virginica' }    {'virginica' }
    141    {'virginica' }    {'virginica' }
    142    {'virginica' }    {'virginica' }
    143    {'virginica' }    {'virginica' }
    144    {'virginica' }    {'virginica' }
    145    {'virginica' }    {'virginica' }
    146    {'virginica' }    {'virginica' }
    147    {'virginica' }    {'virginica' }
    148    {'virginica' }    {'virginica' }
    149    {'virginica' }    {'virginica' }
    150    {'virginica' }    {'virginica' }

[Yumi Iwakami]

コード付きの詳しい説明，ありがとうございます．

MATLABによる機械学習についてもうすこし勉強してみたいと思います．