I am using an audio classifier with the following features
aFE = audioFeatureExtractor("SampleRate",fs, ...
"SpectralDescriptorInput","melSpectrum", ...
"spectralCentroid",true, "spectralSlope",true,"spectralFlux",true,...
"spectralKurtosis",true,"spectralSkewness",true,"pitch",true,...
"harmonicRatio",true,"zerocrossrate",true,"shortTimeEnergy",true,...
"spectralSpread",true,"spectralRolloffPoint",true,...
"spectralCrest",true,"spectralDecrease",true,...
"spectralEntropy",true,"spectralFlatness",true,...
"mfccDeltaDelta",true,"gtcc",true,"gtccDelta",true,...
"gtccDeltaDelta",true,"mfcc",true,"mfccDelta",true);
I use these features to train the following network
% Define the Deep Neural Network
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(100,"OutputMode","last")
fullyConnectedLayer(numel(unique(labelsTrain)))
softmaxLayer
classificationLayer];
% Define the training options
options = trainingOptions("adam", ...
"Shuffle","every-epoch", ...
"ValidationData",{featuresValidation,labelsValidation}, ...
"Plots","training-progress", ...
'InitialLearnRate',1e-3,...
"MaxEpochs",100,...
"Verbose",true);
% Train the Network
net = trainNetwork(featuresTrain,labelsTrain,layers,options);
Here is my question... How do I use the ouput of [idx,scores] = fscmrmr(XX,YY); to assess which features are the most important? I enabled 21 features in 'aFE' but the FeatureVectorLength is 93. How do I correlate the scores and indices returned with the fscmrmr(X,Y) funnction with features I defined in aFE?
