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)
