Split into three set, do not run test set.
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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.
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Madhav Thakker
2021 年 5 月 18 日
Hi Michelle,
The cvpartition(group,'KFold',k) function with k=n creates a random partition for leave-one-out cross-validation on n observations.
Hope this helps.
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