auto_scale=True with regressors errors out

[wangzhishi]

when auto_scale=True with regressors, the following error message pops out:

---

TypeError Traceback (most recent call last)
in
1 from sklearn.preprocessing import MinMaxScaler
2 regressor_min_max_scaler = MinMaxScaler(1, 2.719)
----> 3 df[regressor_col] = regressor_min_max_scaler.fit_transform(df[regressor_col])

~/Desktop/uTS-py/myenv/lib/python3.7/site-packages/sklearn/base.py in fit_transform(self, X, y, **fit_params)
569 if y is None:
570 # fit method of arity 1 (unsupervised transformation)
--> 571 return self.fit(X, **fit_params).transform(X)
572 else:
573 # fit method of arity 2 (supervised transformation)

~/Desktop/uTS-py/myenv/lib/python3.7/site-packages/sklearn/preprocessing/_data.py in fit(self, X, y)
337 # Reset internal state before fitting
338 self._reset()
--> 339 return self.partial_fit(X, y)
340
341 def partial_fit(self, X, y=None):

~/Desktop/uTS-py/myenv/lib/python3.7/site-packages/sklearn/preprocessing/_data.py in partial_fit(self, X, y)
361 """
362 feature_range = self.feature_range
--> 363 if feature_range[0] >= feature_range[1]:
364 raise ValueError("Minimum of desired feature range must be smaller"
365 " than maximum. Got %s." % str(feature_range))

TypeError: 'int' object is not subscriptable

[edwinnglabs]

Auto-scale needs to be revisited later. It is sub-optimal in current version