I am trying to adapt example provided here
https://www.mathworks.com/help/releases/R2017a/nnet/examples/training-a-deep-neural-network-for-digit-classification.html
Except that I want to replace
softnet = trainSoftmaxLayer(feat2,tTrain,'MaxEpochs',400);
With something similar to this
options = trainingOptions('sgdm','MaxEpochs',20,...'InitialLearnRate',0.0001);routputlayer = regressionLayer('Name','routput');trainedROL = trainNetwork(feat2,yTrain,routputlayer,options);
However, I receive the following error:
Error using trainNetwork>iAssertXAndYHaveSameNumberOfObservations (line 604)
X and Y must have the same number of observations.
Error in trainNetwork>iParseInput (line 336)
iAssertXAndYHaveSameNumberOfObservations( X, Y );
Error in trainNetwork (line 68)
[layers, opts, X, Y] = iParseInput(varargin{:});
Error in test (line 176)
trainedROL = trainNetwork(feat2,tTrain,routputlayer,options);
How can I modify the algorithm to do regression rather than classification?
Best Answer