Training and splitting a custom dataset

Hello there, everyone. I recently worked in Matlab using deep learning and made the dataset in the program, but I don't know how to split and train this data

DatasetMatlab.mat .... this dataset , and consist of three parts

parts :-

1- LabelData

2- DataSource

3- LabelDefinitions

Answer 1

[Sulaymon Eshkabilov]

In this case, there are a few ways - cvpartition() and datasample() to split/partition the data into training and test data sets, e.g.:

X = INPUT_Data;
Y = OUTPUT_Data;
rng("default"); % For reproducibility
n = length(Y);
%% cvpartition()
C = cvpartition(n, "HoldOut", 0.25);         % Randomly selected 25% of data are used for testing and 75% for training
INDEXtrain = training(C,1);
INDEXtest = ~ INDEXtrain;
X_test = X(INDEXtest,:);   
Y_test = Y(INDEXtest,:);
X_train = X(INDEXtrain,:); 
Y_train = Y(INDEXtrain,:);
...
 %% datasample()
NSample = 200;   % 200 data sets are taken randomly for training
[Xtrain, Xtrain_Idx] = datasample(XYData, NSample);