Dear All,
I'm traing to train a network with numeric data, it reads a covid-19 Patients data such as Age, weight, gender and temprture, these data in csv format, here is my code
%loading file
filename = "Patient_cardio_COVID.csv";
tbl = readtable(filename,'TextType','String','PreserveVariableNames',true) ;
%Convert the labels for prediction to categorical using the convertvars function.
labelName = "active";
tbl = convertvars(tbl,labelName,'categorical');
categoricalInputNames = {'cardio','smoke', 'Body_Temprature'} ;
tbl = convertvars(tbl,categoricalInputNames,'categorical') ;
classNames = categories(tbl{:,labelName}) ;
%Split Data Set into Training and Validation Sets
%Partition the data set into training, validation, and test partitions. Set aside 15% of the data for validation, and 15% for testing.
numObservations = size(tbl,1) ;
%Determine the number of observations for each partition.
numObservationsTrain = floor(0.7*numObservations) ;
numObservationsValidation = floor(0.15*numObservations);
numObservationsTest = numObservations - numObservationsTrain - numObservationsValidation ;
%Create an array of random indices corresponding to the observations and partition it using the partition sizes
idx = randperm(numObservations);
idxTrain = idx(1:numObservationsTrain);
idxValidation = idx(numObservationsTrain+1:numObservationsTrain+numObservationsValidation);
idxTest = idx(numObservationsTrain+numObservationsValidation+1:end);
%Partition the table of data into training, validation, and testing partitions using the indices
tblTrain = tbl(idxTrain,:) ;
head (tblTrain)
tblValidation = tbl(idxValidation,:);
tblTest = tbl(idxTest,:);
%Define Network Architecture
numFeatures = size(tbl,2) - 1 ;
numClasses = numel(classNames) ;
layers = [
featureInputLayer(numFeatures,'Normalization', 'zscore')
fullyConnectedLayer(50)
batchNormalizationLayer
reluLayer
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];
%Training Options
miniBatchSize = 16;
options = trainingOptions('adam', ...
'MiniBatchSize',miniBatchSize, ...
'Shuffle','every-epoch', ...
'ValidationData',tblValidation, ...
'Plots','training-progress', ...
'Verbose',false);
net = trainNetwork(tblTrain,labelName,layers,options);
at this stage I got this error messsage
"Invalid training data table. For networks with feature input, predictors must be numeric arrays, where each variable of
the table corresponds to one feature"
Any Advice
