def flattenAndLoad_FM_traindata(self,hist_len, cur_week): train_data = flatten_featureset.extract_features_from_sql(self.conn, self.name, self.earliest_date, self.latest_date, self.threshold, self.features, self.weeks, cur_week, hist_len, mode='FM_train') self.X_train = train_data[:,1:] self.Y_train = train_data[:,0]
def flattenAndLoad_traindata(self,lead,lag): train_data = flatten_featureset.extract_features_from_sql(self.conn, self.name, self.earliest_date, self.latest_date, self.threshold, self.features, self.weeks, lead, lag, mode='Train') self.X_train = train_data[:,1:] self.Y_train = train_data[:,0]
def flattenAndLoad_FM_traindata(self, hist_len, cur_week): train_data = flatten_featureset.extract_features_from_sql( self.conn, self.name, self.earliest_date, self.latest_date, self.threshold, self.features, self.weeks, cur_week, hist_len, mode='FM_train') self.X_train = train_data[:, 1:] self.Y_train = train_data[:, 0]
def flattenAndLoad_traindata(self, lead, lag): train_data = flatten_featureset.extract_features_from_sql( self.conn, self.name, self.earliest_date, self.latest_date, self.threshold, self.features, self.weeks, lead, lag, mode='Train') self.X_train = train_data[:, 1:] self.Y_train = train_data[:, 0]