rime.models.Pop

class rime.models.Pop(user_rec=True, item_rec=True, item_pseudo=0.01, user_pseudo=0.01, tie_breaker=0.01)[source]

Bases: object

__init__(user_rec=True, item_rec=True, item_pseudo=0.01, user_pseudo=0.01, tie_breaker=0.01)[source]

Methods

`__init__`([user_rec, item_rec, item_pseudo, ...])
`fit`(D)
`transform`(D)	user_score * item_score = (user_log_bias + item_log_bias).exp()

transform(D)[source]: user_score * item_score = (user_log_bias + item_log_bias).exp()