Crossvalidation¶
Dataset splitting functions.

lightfm.cross_validation.
random_train_test_split
(interactions, test_percentage=0.2, random_state=None)[source]¶ Randomly split interactions between training and testing.
This function takes an interaction set and splits it into two disjoint sets, a training set and a test set. Note that no effort is made to make sure that all items and users with interactions in the test set also have interactions in the training set; this may lead to a partial coldstart problem in the test set.
Parameters:  interactions (a scipy sparse matrix containing interactions) – The interactions to split.
 test_percentage (float, optional) – The fraction of interactions to place in the test set.
 random_state (np.random.RandomState, optional) – The random state used for the shuffle.
Returns: (train, test) – scipy.sparse.COOMatrix) A tuple of (train data, test data)
Return type: (scipy.sparse.COOMatrix,