Classification Learner gives different results every time

If run the classifications learner, get the results, close down the classification learner, immediately open up classification learner again (same data is kept in the work-space, nothing has changed or reloaded), and run the classification again. Why are different results yielded?

Answer 1

[MathWorks Support Team]

The reason for the different results is by using k-fold cross-validation method.

When starting a new session in the Classification Learners App, the default validation method under the 'Step 3' section is 5 folds cross-validation.

This means that MATLAB will randomly partition all of the selected data into 5 equally sized sub-samples. Then it uses 4 partitions to train a model and use the 1 partition left for testing/validation.

The cross-validation process is then repeated 5 times, with each of the 5 sub-samples used exactly once as the validation data.

Therefore, when starting a new session each time, the data will be randomly partitioned into different sub-samples and will have different results.

Refer to the following link for more information on selecting validation method in MATLAB:

https://www.mathworks.com/help/stats/select-data-and-validation-for-classification-problem.html