Too many Arguments for trainNetwork()

Hello Matlab Community,

I'm trying to make a neural network that identifies if the system is in one of two conditions ('Normal' or 'Slugged'- Condition) of a Data Set with Data Points of 13 sensors.

I have a Training Data Set with the size 9 600 000x 14. After I devided it into a Training and a Test set I got 'X_Train' of the size of 13x8640000 for the Input and 'Y_Train' of the size of 1x8640000 for the output. The rest goes into the Training Data Set. For better visualisation:

• Main Data Set 'Gesamttabelle' : 9600000x14
• Training Input 'X_Train': 13x864000
• Training Output 'Y_Train': 1x864000
• Test Input 'X_Test': 13x960000
• Test Output 'Y_Test': 1x96000

That' how I coded the Data Set Editing:

load Gesamttabelle;

%% NN TRAINING/ TEST DATA SET

Data_Set_Shuffled = Gesamttabelle(randperm(size(Gesamttabelle,1)),:);

output = Data_Set_Shuffled(:,14);

output = table2array(output);

input = Data_Set_Shuffled(:,1:13);

% Switch Rows and Coloums
input = rows2vars(input);
output = output';

input(:,1) = [];

% Devide Data Set into Training and Test Sets 
test_range = round(0.9*size(input,2),-2);

X_Train = input(1:13,1:test_range);
Y_Train = categorical(output(1:test_range));

X_Test = input(1:13,test_range:end);
Y_Test = categorical(output(test_range:end));

After that I designed the neurals network architecture and the training parameters

%% DEEP LEARNING NETWORK ARCHITECTURE        
 
hidden_layer_size = 100;

layers = [...
    sequenceInputLayer(13)
    fullyConnectedLayer(hidden_layer_size)
    reluLayer
    fullyConnectedLayer(hidden_layer_size)
    reluLayer
    fullyConnectedLayer(2)
    softmaxLayer
    classificationLayer];

%% TRAINING PARAMETER

Batch_Size = 1000;
Epochs = 50;

options = trainingOptions('adam', ...  
    'MaxEpochs',Epochs, ...
    'MiniBatchSize',Batch_Size, ...
    'GradientThreshold',1, ...
    'InitialLearnRate',0.001, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropPeriod',125, ...
    'LearnRateDropFactor',0.2, ...
    'Verbose',0, ...
    'Plots', 'training-progress',...
    'ExecutionEnvironment','cpu');

Now, when I try to call the the trainNetwork()- function

NN = trainNetwork(X_Train,Y_Train,layers,options);

I get the Error message:

Error using trainNetwork (line 184)
Too many input arguments.

Error in SuO_NN_Train (line 93)
SuO_NN_raw = trainNetwork(X_Train,Y_Train,layers,options);

Caused by:
    Error using nnet.internal.cnn.trainNetwork.DLTInputParser>iParseInputArguments (line 83)
    Too many input arguments.
    

I use MATLAB R2021a. Can anybody please help me out?

Answer 1

[Benjamin Thompson]

See the MATLAB help article on "Support Variable Number of Inputs", you probably want to use varargin. Also "Parse Function Inputs".

[long feifei]

The answer is bad