def __init__(self, nbr_users = 4, nbr_items = 6, parameters = False, filename = False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.nbr_epochs = 200 self.feature_init = 0.1 self.learning_rate = 0.01 self.learning_rate_users = 0.01 self.learning_rate_items = 0.01 self.K_users = 0.1 self.K_items = 0.1 self.K_bias = 0.007 self.dimensionality = 40 if parameters: self.set_parameters(parameters) self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None
def __init__(self, nbr_users=4, nbr_items=6, parameters=False, filename=False): MFRecommender.__init__(self, nbr_users, nbr_items, parameters) # Initialize the training parameters with the default value self.min_epochs = 275 self.max_epochs = 275 self.min_improvement = 0.0001 self.feature_init = 0.1 self.learning_rate = 0.001 self.learning_rate_users = 0.001 self.learning_rate_items = 0.001 self.K = 0.05 self.K2 = 0.01 self.K3 = 0.01 self.dimensionality = 40 if parameters: self.set_parameters(parameters) self.batch_size = 10 self.rmse_history = np.zeros(self.max_epochs) self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.mongodb_iterator = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None
def __init__(self, nbr_users = 4, nbr_items = 6, parameters = False, filename = False): MFRecommender.__init__(self, nbr_users, nbr_items, parameters) # Initialize the training parameters with the default value self.min_epochs = 275 self.max_epochs = 275 self.min_improvement = 0.0001 self.feature_init = 0.1 self.learning_rate = 0.001 self.learning_rate_users = 0.001 self.learning_rate_items = 0.001 self.K = 0.05 self.K2 = 0.01 self.K3 = 0.01 self.dimensionality = 40 if parameters: self.set_parameters(parameters) self.batch_size = 10 self.rmse_history = np.zeros(self.max_epochs) self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.mongodb_iterator = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None
def __init__(self, nbr_users=4, nbr_items=6, parameters=False, filename=False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.nbr_epochs = 200 self.feature_init = 0.1 self.learning_rate = 0.01 self.learning_rate_users = 0.01 self.learning_rate_items = 0.01 self.K_users = 0.1 self.K_items = 0.1 self.K_bias = 0.007 self.dimensionality = 40 if parameters: self.set_parameters(parameters) self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None
def __init__(self, nbr_users = 4, nbr_items = 6, parameters = False, filename = False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.dimensionality = 150 if parameters: self.set_parameters(parameters)
def __init__(self, nbr_users = 4, nbr_items = 6, parameters = False, filename = False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.k = 80 self.k_min = 2 self.sim_threshold = 0.18 self.dimensionality = 40 if parameters: self.set_parameters(parameters)
def __init__(self, nbr_users=4, nbr_items=6, parameters=False, filename=False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.dimensionality = 150 if parameters: self.set_parameters(parameters)
def __init__(self, nbr_users=4, nbr_items=6, parameters=False, filename=False): MFRecommender.__init__(self, nbr_users, nbr_items, filename) # Initialize the training parameters with the default value self.k = 80 self.k_min = 2 self.sim_threshold = 0.18 self.dimensionality = 40 if parameters: self.set_parameters(parameters)
def __init__(self, nbr_users=4, nbr_items=6, parameters=None): MFRecommender.__init__(self, nbr_users, nbr_items, parameters) # Initialize the training parameters with the default value self.nbr_epochs = 20 self.feature_init = 0.1 self.K = 0.025 self.dimensionality = 20 self.neighborhood = 500 self.batch_size = 10 self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.mongodb_iterator = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None if parameters: self.set_parameters(parameters)
def __init__(self, nbr_users = 4, nbr_items = 6, parameters = None): MFRecommender.__init__(self, nbr_users, nbr_items, parameters) # Initialize the training parameters with the default value self.nbr_epochs = 20 self.feature_init = 0.1 self.K = 0.025 self.dimensionality = 20 self.neighborhood = 500 self.batch_size = 10 self.rating_cache = None self.nbr_ratings = None self.global_avg = None self.mongodb_iterator = None self.components_mean = None self.N = None self.items_feedback = None self.feedback_rated = None self.feedback_hash = None if parameters: self.set_parameters(parameters)