Split into three set, do not run test set.
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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?
Madhav Thakker on 18 May 2021
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.