import numpy as np
from sklearn.preprocessing import MinMaxScaler
a=np.array([1,2,3,4,5], dtype='float64')
print('a-1D:', a, a.shape)
a=a.reshape(-1,1)
print('a-2D:', a, a.shape)
scaler_2 = MinMaxScaler(feature_range=(0, 1))
scaled = scaler_2.fit_transform(a)
print('a-transformed:', scaled)
inv_a = scaler_2.inverse_transform(scaled)
print('a-inversed:',inv_a)
a-1D:
[1. 2. 3. 4. 5.] (5,)
a-2D:
[[1.]
[2.]
[3.]
[4.]
[5.]] (5, 1)
a-transformed:
[[0. ]
[0.25]
[0.5 ]
[0.75]
[1. ]]
a-inversed:
[[1.]
[2.]
[3.]
[4.]
[5.]]