evalModel | R Documentation |
Creates the dataset split for evaluation where ratings of each user are uniformly distributed over k random folds. The function returns the list of items that are assigned to each fold, such that algorithms can be compared on the same train/test splits.
evalModel(data, folds)
data |
dataset, of class |
folds |
The number of folds to use in the k-fold cross validation, of class |
An object of class evalModel-class
.
evalModel-class
, evalRec
, _ds
.
x <- matrix(sample(c(0:5), size = 200, replace = TRUE, prob = c(.6,.08,.08,.08,.08,.08)), nrow = 20, byrow = TRUE) d <- defineData(x) my_2_folds <- evalModel(d, 2) #output class evalModel. my_2_folds # 2 - fold cross validation model on the dataset with 20 users and 10 items. my_2_folds@data #the dataset. my_2_folds@folds #the number of folds in the model. my_2_folds@fold_indices #the index of each item in the fold.
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