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CV cross validation object
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a=cv(algo,hyperParam) Returns a cv object on algorithm algo using with
given Hyperparameters.
Possible hyperparameters (with defaults):
folds=5 - number of folds
repeats=1 - can do n*CV for reduced variance
balanced=0 - determines if cv shall be balanced (same number of
positives in each fold)
store_all=1 - determines if models trained in all folds shall be stored
output_train_error=0 - determines wheter to output training error on each fold
(else cv error, i.e test left out fold as default)
train_on_fold=0 - determines to test on left out fold and train on the
rest (set to true for the opposite).
store_trialbytrial=0 - whether to store the field a.trialbytrial, the rows of
which are [i, foldnumber, y_i, f(x_i)] for each index
i of a data point on which the algorithm was tested
Model:
child - stored in child algorithm
Methods:
train - selfexplanatory
test - selfexplanatory