CollaborativeFilteringModel train

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train(self, frame, source_column_name, dest_column_name, weight_column_name, max_steps=10, regularization=0.5, alpha=0.5, num_factors=3, use_implicit=False, num_user_blocks=2, num_item_block=3, target_rmse=0.05)

Collaborative filtering (ALS) model

Parameters:

frame : Frame

source_column_name : unicode

source column name.

dest_column_name : unicode

destination column name.

weight_column_name : unicode

weight column name.

max_steps : int32 (default=10)

max number of super-steps (max iterations) before the algorithm terminates. Default = 10

regularization : float32 (default=0.5)

float value between 0 .. 1

alpha : float64 (default=0.5)

double value between 0 .. 1

num_factors : int32 (default=3)

number of the desired factors (rank)

use_implicit : bool (default=False)

use implicit preference

num_user_blocks : int32 (default=2)

number of user blocks

num_item_block : int32 (default=3)

number of item blocks

target_rmse : float64 (default=0.05)

target RMSE

Examples

See :doc: ‘here <new>’ for examples.