def run(self):
logging.info('Begin train '+self.name)
start=datetime.now()
boost_instance=mboost.Mboost(self.config)
boost_instance.level_predict(self.clf,self.level,self.name,self.X_0,self.X_1,self.predict_X,self.predict_uid)
end=datetime.now()
logging.info('End train '+self.name+", cost time: "+str(float((end-start).seconds)/60.0)+"min / "+str(float((end-start).seconds))+"s")
def run(self):
logging.info('Begin train ' + self.name)
start = datetime.now()
boost_instance = mboost.Mboost(self.config)
boost_instance.level_train(
self.clf, self.level, self.name, self.X_0, self.X_1, self.uid_0,
self.uid_1) #initiate Mboost, call level_train method
end = datetime.now()
logging.info('End train ' + self.name + ", cost time: " +
str(float((end - start).seconds) / 60.0) + "min / " +
str(float((end - start).seconds)) + "s")
def run(self):
logging.info('Begin train ' + self.name)
start = datetime.now()
boost_instance = mboost.Mboost(self.config)
boost_instance.xgb_level_train(self.level, self.name, self.X_0,
self.X_1, self.uid_0, self.uid_1,
self.params, self.round)
end = datetime.now()
logging.info('End train ' + self.name + ", cost time: " +
str(float((end - start).seconds) / 60.0) + "min / " +
str(float((end - start).seconds)) + "s")
