Is it possible to perfrom cross validation for k = 1 fold (or 1 fold cross validation)
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jaypal singh
on 10 Jun 2020
Commented: jaypal singh
on 13 Jun 2020
In Matlab 2018. I have used cross-validation method. in Classfier learner app I found that cross validation is given for fold 2- fold 5. I want to perform K=1 fold .
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Anish Walia
on 11 Jun 2020
Though it is possible but it does not have any meaning
In K-Fold cross validation method, we divide the data in K folds. Then we use K-1 folds for training it and evaluate/test it on the 1 fold and then repeat it K times with unique fold for evaluating in each iteration.
So K-Fold cross validation on 1 fold would mean dividing data in 1 fold and using 0 (K-1) fold for training, which basically means not training and just testing on that fold
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Anish Walia
on 11 Jun 2020
Okay so i suppose you misunderstood the problem.
The problem just needs 10 fold cross validation.
So divide the data in 10 folds, and basically plot the sensitivity for each fold.
Retain one fold as hold out, train on remaining 9 and plot the sensitivity for the hold out fold.
Then retain another unique fold as hold out, train on remaining 9 and plot sensitivity for this fold as fold 2 in graph
Similiarly repeat this 10 times with taking unique hold out folds and plot as fold 3, fold 4...., fold 10
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