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

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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?

Answers (1)

Prince Kumar
Prince Kumar on 21 Jan 2022
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
Hope this helps!

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