Compute the cross-validation emprirical and generalization scores.
Usage
LPO_best_models(X, y, clf, p = 1, lfolds = NULL, return.all = FALSE, nk = 20)
Arguments
- X:
the data matrix with variables in the rows and observations in the columns
- y:
the response vector
- clf:
clf
- lfolds:
leave one out folds for cross-validation
- return.all:
return all results from the crossvalidation for feature stability testing
Value
a list containing generalisation scores for each fold as well as a matrix with the mean values.