def readConfiguration(self):
super(SGL, self).readConfiguration()
args = config.LineConfig(self.config['SGL'])
self.ssl_reg = float(args['-lambda'])
self.drop_rate = float(args['-droprate'])
self.aug_type = int(args['-augtype'])
self.ssl_temp = float(args['-temp'])
def readConfiguration(self):
super(SEPT, self).readConfiguration()
args = config.LineConfig(self.config['SEPT'])
self.n_layers = int(args['-n_layer'])
self.ss_rate = float(args['-ss_rate'])
self.drop_rate = float(args['-drop_rate'])
self.instance_cnt = int(args['-ins_cnt'])
def readConfiguration(self):
super(IterativeRecommender, self).readConfiguration()
# set the reduced dimension
self.emb_size = int(self.config['num.factors'])
# set maximum iteration
self.maxEpoch = int(self.config['num.max.epoch'])
# set learning rate
learningRate = config.LineConfig(self.config['learnRate'])
self.lRate = float(learningRate['-init'])
self.maxLRate = float(learningRate['-max'])
if self.evalSettings.contains('-tf'):
self.batch_size = int(self.config['batch_size'])
# regularization parameter
regular = config.LineConfig(self.config['reg.lambda'])
self.regU, self.regI, self.regB = float(regular['-u']), float(
regular['-i']), float(regular['-b'])
def readConfiguration(self):
super(CoFactor, self).readConfiguration()
extraSettings = config.LineConfig(self.config['CoFactor'])
self.negCount = int(
extraSettings['-k']) #the number of negative samples
if self.negCount < 1:
self.negCount = 1
self.regR = float(extraSettings['-gamma'])
self.filter = int(extraSettings['-filter'])
def readConfiguration(self):
super(ESRF, self).readConfiguration()
args = config.LineConfig(self.config['ESRF'])
self.K = int(
args['-K']) #controling the magnitude of adversarial learning
self.beta = float(args['-beta']) #the number of alternative neighbors
self.n_layers_D = int(
args['-n_layer']
) #the number of layers of the recommendation module (discriminator)
def readConfiguration(self):
super(CUNE_MF, self).readConfiguration()
options = config.LineConfig(self.config['CUNE-MF'])
self.walkCount = int(options['-T'])
self.walkLength = int(options['-L'])
self.walkDim = int(options['-l'])
self.winSize = int(options['-w'])
self.topK = int(options['-k'])
self.epoch = int(options['-ep'])
self.alpha = float(options['-a'])
def readConfiguration(self):
super(IF_BPR, self).readConfiguration()
options = config.LineConfig(self.config['IF_BPR'])
self.walkLength = int(options['-L'])
self.walkDim = int(options['-l'])
self.winSize = int(options['-w'])
self.topK = int(options['-k'])
self.alpha = float(options['-a'])
self.epoch = int(options['-ep'])
self.neg = int(options['-neg'])
self.rate = float(options['-r'])
def readConfiguration(self):
super(LOCABAL, self).readConfiguration()
alpha = config.LineConfig(self.config['LOCABAL'])
self.alpha = float(alpha['-alpha'])
def readConfiguration(self):
super(TBPR, self).readConfiguration()
options = config.LineConfig(self.config['TBPR'])
self.regT = float(options['-regT'])
def readConfiguration(self):
super(BUIR, self).readConfiguration()
args = config.LineConfig(self.config['BUIR'])
self.n_layers = int(args['-n_layer'])
self.tau = float(args['-tau'])
self.drop_rate = float(args['-drop_rate'])
def readConfiguration(self):
super(DiffNet, self).readConfiguration()
args = config.LineConfig(self.config['DiffNet'])
self.n_layers = int(
args['-n_layer']
) #the number of layers of the recommendation module (discriminator)
def readConfiguration(self):
super(SocialRecommender, self).readConfiguration()
regular = config.LineConfig(self.config['reg.lambda'])
self.regS = float(regular['-s'])
def readConfiguration(self):
super(SoReg, self).readConfiguration()
alpha = config.LineConfig(self.config['SoReg'])
self.alpha = float(alpha['-alpha'])
def readConfiguration(self):
super(RSTE, self).readConfiguration()
alpha = config.LineConfig(self.config['RSTE'])
self.alpha = float(alpha['-alpha'])
def readConfiguration(self):
super(CHER, self).readConfiguration()
args = config.LineConfig(self.config['CHER'])
self.ssl_reg = float(args['-lambda'])
self.eps = float(args['-eps'])
self.n_layers = int(args['-n_layer'])
def readConfiguration(self):
super(CDAE, self).readConfiguration()
args = config.LineConfig(self.config['CDAE'])
self.corruption_level = float(args['-co'])
self.n_hidden = int(args['-nh'])
def readConfiguration(self):
super(MHCN, self).readConfiguration()
args = config.LineConfig(self.config['MHCN'])
self.n_layers = int(args['-n_layer'])
self.ss_rate = float(args['-ss_rate'])
def readConfiguration(self):
super(SREE, self).readConfiguration()
par = config.LineConfig(self.config['SREE'])
self.alpha = float(par['-alpha'])
def readConfiguration(self):
super(SoRec, self).readConfiguration()
regZ = config.LineConfig(self.config['SoRec'])
self.regZ = float( regZ['-z'])
def readConfiguration(self):
super(APR, self).readConfiguration()
args = config.LineConfig(self.config['APR'])
self.eps = float(args['-eps'])
self.regAdv = float(args['-regA'])
self.advEpoch = int(args['-advEpoch'])
