Spliting ground truth data into 70% training, 20% validation and 10% Testingdata

Question

Abdussalam Elhanashi 2020-5-21

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/529548-spliting-ground-truth-data-into-70-training-20-validation-and-10-testingdata

回答： Shantanu Dixit 2024-12-27

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Hi guys

i am looking for spliting data from ground truth file for following code

70% training, 20% validation and 10% Testingdata

load('gTruth.mat')
Fruits = selectLabels(gTruth,{'orange','Apple'});
if isfolder(fullfile('ExperimentData'))
    cd ExperimentData
else
     mkdir ExperimentData
end 
  
 
addpath('ExperimentData');
splitFolder = true;
if splitFolder
    valFolderName = "ExperimentData";
    
    files = dir(fullfile(valFolderName));
    N = length(files);
    tf=randperm(N)>(0.20*N);
    mkdir TrainingData;
    mkdir ValidationData;
    mkdir TestingData;
    for i=3:length(tf)
        files_re = files(i).name;
        if tf(i) == 3
            copyfile (fullfile(valFolderName,files_re),'TrainingData')
        else
            copyfile (fullfile(valFolderName,files_re),'Validation')
        ifelse
            copyfile (fullfile(valFolderName,files_re),'TestingData')
        end
    end
end

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Answer 1

Shantanu Dixit 2024-12-27

0
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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/529548-spliting-ground-truth-data-into-70-training-20-validation-and-10-testingdata#answer_1556529

在 MATLAB Online 中打开

Hi Abdussalam,

To split your ground truth data into training, validation, and testing sets, you can use the 'randperm' function to randomly shuffle the data and 'copyfile' to copy the data from the original data to the corresponding splits.

You can refer to the below code snippet to split data in 70:20:10 ratio

% Generate a random permutation of indices
% N = total data points
indices = randperm(N);
% Determine the number of files for each split
numTrain = round(0.7 * N);
numVal = round(0.2 * N);
numTest = N - numTrain - numVal;
mkdir('TrainingData');
mkdir('ValidationData');
mkdir('TestingData');
% Assuming ExperimentData contains the data files
for i = 1:numTrain
    copyfile(fullfile('ExperimentData', files(indices(i)).name), 'TrainingData');
end
for i = numTrain+1:numTrain+numVal
    copyfile(fullfile('ExperimentData', files(indices(i)).name), 'ValidationData');
end
for i = numTrain+numVal+1:N
    copyfile(fullfile('ExperimentData', files(indices(i)).name), 'TestingData');
end