Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- Parameters:
- X : array-like, shape [n_samples, n_features]
- x -= x.min()
- x /= x.ptp()
- mn, mx = x.min(), x.max()
- x_scaled = (x - mn) / (mx - mn)
- mn, ptp = x.min(), x.ptp()
- x_scaled = (x - mn) / ptp
- from sklearn.preprocessing import minmax_scale
- minmax_scale(array)
Add Comment
Please, Sign In to add comment
