You can perform a K-fold cross validation for the 'fitlm' function into K folds using the 'crossval' function. In order to do so, define a predictor function handle which uses 'fitlm' and then pass the predictor function handle to the 'crossval' function.
Mentioned below is a sample code snippet to do so:
% prediction function given training and testing instances
>> fcn = @(Xtr, Ytr, Xte) predict( fitlm(Xtr,Ytr), Xte);
% perform cross-validation, and return average MSE across folds
>> mse = crossval('mse', X, Y,'Predfun',fcn, 'kfold',10);
% compute root mean squared error
>> avrg_rmse = sqrt(mse)
Regards,
Shubham
