import alpenglow.Getter as rs
import alpenglow.offline
[docs]class FactorModel(alpenglow.offline.OfflineModel):
def _fit(self, recommender_data, users, items, matrix):
model = rs.FactorModel(**self.parameter_defaults(
begin_min=-0.01,
begin_max=0.01,
dimension=10,
initialize_all=False,
seed=254938879,
))
updater = rs.FactorModelGradientUpdater(**self.parameter_defaults(
learning_rate=0.05,
regularization_rate=0.0
))
updater.set_model(model)
negative_sample_generator = rs.UniformNegativeSampleGenerator(**self.parameter_defaults(
negative_rate=9
))
negative_sample_generator.set_train_matrix(matrix)
negative_sample_generator.set_items(items)
point_wise = rs.ObjectiveMSE()
gradient_computer = rs.GradientComputerPointWise()
gradient_computer.set_objective(point_wise)
gradient_computer.set_model(model)
learner = rs.OfflineIteratingImplicitLearner(**self.parameter_defaults(
seed=254938879,
number_of_iterations=20,
))
learner.set_gradient_computer(gradient_computer)
learner.set_negative_sample_generator(negative_sample_generator)
learner.set_model(model)
learner.set_recommender_data(recommender_data)
learner.add_gradient_updater(updater)
return (model, learner)