Split into three set, do not run test set.

Hello.

I was wondering, in a NN, i understand you can split the dataset using for example divederand or divideblock. But how do you "save" the test set from running when training ? Also i understand you can divde and hold out part of the dataset with for example c = cvpartition(n,'Holdout',p), but this only divides into two parts training and test set. I am new to ML, so this is all a bit confusing still i hope this makes sense to you. Also what is the difference between cross validation and holding out one part of the dataset?

Regards Michelle.

Answer 1

[Madhav Thakker]

Hi Michelle,

The cvpartition(group,'KFold',k) function with k=n creates a random partition for leave-one-out cross-validation on n observations.

To know more about this, have a look at https://in.mathworks.com/discovery/cross-validation.html.

Hope this helps.