Open aerinkim opened 7 years ago
This causes few issues like 1) being unable to broadcast 2) need to write different version of cost function calculation: (1-y).values.flatten() instead of (1-y)
It's better to unify the data type as numpy array to reduce confusion from users.
One quick fix would be using
from sklearn.preprocessing import PolynomialFeatures
PolynomialFeatures(6)
This causes few issues like 1) being unable to broadcast 2) need to write different version of cost function calculation: (1-y).values.flatten() instead of (1-y)
It's better to unify the data type as numpy array to reduce confusion from users.