How to feed a feature matrix for each class in multiclass classification?

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NASRIN AKTER
NASRIN AKTER 2021 年 10 月 13 日
回答済み: Prince Kumar 2022 年 1 月 21 日
Hello
I am using 'emd' for feature extraction. In my case, I will create 5 IMFs and extract 2 features from each so it would be a 5x2 matrix for each class label. How do I feed that to a multiclass classifier?

回答 (1 件)

Prince Kumar
Prince Kumar 2022 年 1 月 21 日
Hi,
You can feed the input matrix like you do it binary classifier or any classifier.
Please refer the following code for better understanding:
load fisheriris
Mdl = fitctree(meas,species)
Mdl =
ClassificationTree ResponseName: 'Y' CategoricalPredictors: [] ClassNames: {'setosa' 'versicolor' 'virginica'} ScoreTransform: 'none' NumObservations: 150 Properties, Methods
After you load the fisheriris dataset, you get meas (150x4) as input matrix and species(150x1) as target array.
Now you simply call "fitctree" to train a multiclass decision tree.
You can now use "predict" function to do the classification on the trained classifier.
X = [4.85,3.4,1.3,0.22];
label = predict(Mdl,X)
label = 1×1 cell array
{'setosa'}
Hope this helps!

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