recommendation/model_reco.py
def create_model(self):
		"""
		Build and compile a MasterModel depending on the method asked
		:return:
		"""
		if self.method == "gmf":
			self.model = GMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								  self.regs).get_model()
		elif self.method == "mf":
			self.model = MFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								 self.regs).get_model()
		elif self.method == "neumf":
			self.model = NeuMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
									self.regs).get_model()
		elif self.method == "nnmf":
			self.model = NNMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								   self.regs).get_model()
		else:
			self.model = None
			raise Exception('Wgrong Argument ! : must be among "gmf", "mf", "neumf", "nnmf"')

		self.model.compile('adam', 'mean_squared_error')

		Build and compile a MasterModel depending on the method asked
		:return:
		
Build and compile a MasterModel depending on the method asked
Build and compile a MasterModel depending on the method asked
def create_model(self):
		if self.method == "gmf":
			self.model = GMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								  self.regs).get_model()
		elif self.method == "mf":
			self.model = MFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								 self.regs).get_model()
		elif self.method == "neumf":
			self.model = NeuMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
									self.regs).get_model()
		elif self.method == "nnmf":
			self.model = NNMFModel(self.num_users, self.num_tweets, self.num_factors_user, self.num_factors_item,
								   self.regs).get_model()
		else:
			self.model = None
			raise Exception('Wgrong Argument ! : must be among "gmf", "mf", "neumf", "nnmf"')
		self.model.compile('adam', 'mean_squared_error')
def create_model ( self ) : if self . method == "gmf" : self . model = GMFModel ( self . num_users , self . num_tweets , self . num_factors_user , self . num_factors_item , self . regs ) . get_model ( ) elif self . method == "mf" : self . model = MFModel ( self . num_users , self . num_tweets , self . num_factors_user , self . num_factors_item , self . regs ) . get_model ( ) elif self . method == "neumf" : self . model = NeuMFModel ( self . num_users , self . num_tweets , self . num_factors_user , self . num_factors_item , self . regs ) . get_model ( ) elif self . method == "nnmf" : self . model = NNMFModel ( self . num_users , self . num_tweets , self . num_factors_user , self . num_factors_item , self . regs ) . get_model ( ) else : self . model = None raise Exception ( 'Wgrong Argument ! : must be among "gmf", "mf", "neumf", "nnmf"' ) self . model . compile ( 'adam' , 'mean_squared_error' )
Build and compile a MasterModel depending on the method asked
Build and compile a MasterModel depending on the method asked
"""
		Build and compile a MasterModel depending on the method asked
		:return:
		"""
None
self