min max scaler sklearn
from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
scaler.fit_transform(X_train)
scaler.transform(X_test)
min max scaler sklearn
from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
scaler.fit_transform(X_train)
scaler.transform(X_test)
Scaling features to a range
# Scaling features to a range using MinMaxScaler
X_train = np.array([[ 1., -1., 2.],
[ 2., 0., 0.],
[ 0., 1., -1.]])
min_max_scaler = preprocessing.MinMaxScaler()
X_train_minmax = min_max_scaler.fit_transform(X_train)
X_train_minmax
# array([[0.5 , 0. , 1. ],
# [1. , 0.5 , 0.33333333],
# [0. , 1. , 0. ]])
X_test = np.array([[-3., -1., 4.]])
X_test_minmax = min_max_scaler.transform(X_test)
X_test_minmax
# array([[-1.5 , 0. , 1.66666667]])
min_max_scaler.scale_
# array([0.5 , 0.5 , 0.33...])
min_max_scaler.min_
# array([0. , 0.5 , 0.33...])
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