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]
