Error: Unused Output Layer

This is the full error I'm getting: Error using trainNetwork (line 150)

Invalid network.

Error in train (line 12)

Caused by:

Network: Missing output layer. The network must have one output layer.

Layer 4: Unused output. Each layer output must be connected to the input of another layer.

X is a 5 by 30 matrix that I'm trying to run through a relu, then a fully connected layer, and then a softmax to label the data as 0 or 1. I'm confused on why the softmaxLayer isn't taking in the data from the fullyConnectedLayer.

This is the function I'm trying to run.

function [trained_net] = train(X,Y)

% creates adam optimizer

options = trainingOptions('adam', 'InitialLearnRate',3e-4, ...

'SquaredGradientDecayFactor',0.99, 'MaxEpochs',20, ...

'MiniBatchSize',10, 'Plots','training-progress');

% creates layers

layers = [sequenceInputLayer(5)

reluLayer

fullyConnectedLayer(1)

softmaxLayer];

% trains network

trained_net = trainNetwork(X,Y,layers,options);

Answer 1

[Elaine Todd]

Turns out that even though Softmax is in the output layer category, it isn't counted as an output. I added in a classification output layer after the softmax and it runs now.

Answer 2

[Harsha Priya Daggubati]

Hi,

I guess the issue is with fullConnectedLayer's outputSize, as it needs to be equal to the number of classes your network needs to classify. Try changing it to 2 and check whether it works.

[Elaine Todd]

That didn't fix it. Thanks for answering though.