Invalid validation data table. For networks with feature input, predictors must be numeric arrays, where each variable of the table corresponds to one feature.

Question

adib ikhwan 2022-12-22

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1883002-invalid-validation-data-table-for-networks-with-feature-input-predictors-must-be-numeric-arrays-w

回答： Rohit 2023-3-23

Data1.xlsx

Hello, I am new to matlab. I want to ask what to do if there is an invalid validation data table error. This is my code

filename = "Data1.txt";

tbl = readtable(filename,'TextType','String');

labelName = "output";

tbl = convertvars(tbl,labelName,'categorical');

head(tbl)

categoricalInputNames = ["class" "fractaldimension"];

tbl = convertvars(tbl,categoricalInputNames,'categorical');

for i = 1:numel(categoricalInputNames)

name = categoricalInputNames(i);

oh = onehotencode(tbl(:,name));

tbl = addvars(tbl,oh,'After',name);

tbl(:,name) = [];

end

tbl = splitvars(tbl);

head(tbl)

classNames = categories(tbl{:,labelName});

numObservations = size(tbl,1);

numObservationsTrain = floor(0.7*numObservations);

numObservationsValidation = floor(0.15*numObservations);

numObservationsTest = numObservations - numObservationsTrain - numObservationsValidation;

idx = randperm(numObservations);

idxTrain = idx(1:numObservationsTrain);

idxValidation = idx(numObservationsTrain+1:numObservationsTrain+numObservationsValidation);

idxTest = idx(numObservationsTrain+numObservationsValidation+1:end);

tblTrain = tbl(idxTrain,:);

tblValidation = tbl(idxValidation,:);

tblTest = tbl(idxTest,:);

numFeatures = size(tbl,2) - 1;

numClasses = numel(classNames);

layers = [

featureInputLayer(numFeatures,'Normalization', 'zscore')

fullyConnectedLayer(83)

batchNormalizationLayer

reluLayer

fullyConnectedLayer(numClasses)

softmaxLayer

classificationLayer];

miniBatchSize = 16;

options = trainingOptions('adam', ...

'MiniBatchSize',miniBatchSize, ...

'Shuffle','every-epoch', ...

'ValidationData',tblValidation, ...

'Plots','training-progress', ...

'Verbose',false);

net = trainNetwork(tblTrain,labelName,layers,options);

Invalid validation data table. For networks with feature input, predictors must be numeric arrays, where each

variable of the table corresponds to one feature.

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Answer 1

Rohit 2023-3-23

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1883002-invalid-validation-data-table-for-networks-with-feature-input-predictors-must-be-numeric-arrays-w#answer_1199280

在 MATLAB Online 中打开

Hi Adib,

As mentioned in this documentation: https://www.mathworks.com/help/deeplearning/ref/trainingoptions.html , you need to specify the validation data as a datastore, table, or the cell array {predictors,responses}, where predictors contains the validation predictors and responses contains the validation responses.

So, you need to modify code as shown below to get rid of error and start the training.

options = trainingOptions('adam', ...
    'MiniBatchSize',miniBatchSize, ...
    'Shuffle','every-epoch', ...
    'ValidationData',{tblValidation,tblValidation(:,labelName)} ,... % passing validation date as cell array of predictors and responses
    'Plots','training-progress', ...
    'Verbose',false);