Help ME ! Error in feature input layer in CNN, Number of observations in X and Y disagree

I am trying to use a deep neural network in Matlab. However, I get the error:

Number of observations in X and Y disagree.

Below is my current implementation:

[inputs, targets] = load_data();
inputs = inputs'; % size : 18000*10
targets = targets'; % size : 18000*5
randDataNum = 0.15*18000;
%% Validation Data
idx_val = randperm(size(inputs,1),randDataNum);
xVal = inputs(idx_val,:);
inputs(idx_val,:) = [];
yVal = targets(idx_val,:);
targets(idx_val,:) = [];
%% Test Data
idx_test = randperm(size(inputs,1),randDataNum);
xTest = inputs(idx_test,:);
inputs(idx_test,:) = [];
yTest = targets(idx_test,:);
targets(idx_test,:) = [];
%% Define Network Architecture
% Define the convolutional neural network architecture.
layers = [
    featureInputLayer(10,'Name','inputs')
    fullyConnectedLayer(30) % 384 refers to number of neurons in next FC hidden layer
    batchNormalizationLayer
    reluLayer
    fullyConnectedLayer(30) % 384 refers to number of neurons in next FC hidden layer
    reluLayer
    fullyConnectedLayer(5) % 2 refers to number of neurons in next output layer (number of output classes)
    regressionLayer];
options = trainingOptions('adam',...
    'InitialLearnRate', 0.0001, ...
    'MiniBatchSize',16, ...
    'Shuffle','every-epoch', ...
    'MaxEpochs',500, ...
    'Verbose',false,...
    'Plots','training-progress',...
    'ValidationData',{xVal,yVal'});
net = trainNetwork(inputs,targets,layers,options);

how can i fix this error ?

I am using MATLAB 2021b

[Fahad Abdul Wahid]

I've some doubts regarding your function. I'm learning deep learning and wanted to know in the below function

featureInputLayer(10,'Name','inputs') - what does 10 signify?

fullyConnectedLayer(30) what does 30 signify?

fullyConnectedLayer(5) what does 5 signify?

why is there two fully connected layer? What happens when you have only 1 fully connected layer?

Answer 1

[Cris LaPierre]

I see the error in this line:

'ValidationData',{xVal,yVal'});
%                          ^

You are transposing yVal. Assuming your input and target variables are the size you say, this is unnecessary, and causing your number of observations to disagree. Remove the apostraphe, and it should run.

[Amir Hossein Asadian]

Hi Chris

Thank you so much, it was fixed and my problem was solved :)

[nagihan yagmur]

What is the content of the target data? I am also facing a problem. the target of my dataset consists of 5 different classes. Is yours like this too? can you help me

[Cris LaPierre]

@nagihan yagmur please share the same information as the OP so we can help you. Also, if you create a new question, it will get more eyes on it, as this one has an accepted answer.

Answer 2

[Sulaymon Eshkabilov]

As I see in your code the X and Y have mismacthed sizes:

inputs = inputs'; % size : 18000*10
targets = targets'; % size : 18000*5

Make sure that they have the same size when you feed them in trainNetwork().

[Sulaymon Eshkabilov]

Another point is a proper use of size() command, while selecting some data for validation and testing using random number generator, i.e., randperm().

Answer 3

[Arman Ali]

@Amir Hossein Asadian can you contact me at [e-mail] , need your help. Thank you