Matlab code for 10-fold Cross Validation performance for individuall fold

I want to evaluate the performance of each fold of 10 fold cross validation method. I want to calculate Acurract of each fold in 10 fold cross validation. Pls provide the code if you have.

Answer 1

[Omega]

Hi Jaypal,

I can help you with the necessary steps to evaluate the accuracy of individual folds in 10-fold Cross validation. You can refer to steps mentioned below:

• Load your data into MATLAB, ensure that it includes features and class labels.
• Use "cvpartition" with "KFold", set to 10, to create 10-fold cross-validation partitions.
• Create an array to store accuracy for each fold and iterate over each fold.
• For each iteration use "training" and "test" methods to get indices for training and test data for the current fold and fit your classifier using the training data. Use the model to predict on the test data and calculate accuracy by comparing predictions with actual test labels and store it.
• If you would like to compute the overall performance, you can do so by calculating the mean accuracy of across all folds.

You can learn more by going through the following documentation links:

• cvpartition: https://www.mathworks.com/help/stats/cvpartition.html
• training: https://www.mathworks.com/help/stats/cvpartition.training.html
• test: https://www.mathworks.com/help/stats/cvpartition.test.html