Answers for "scaling techniques sklearn"

1

min max scaler sklearn

from sklearn.preprocessing import MinMaxScaler

scaler = MinMaxScaler()
scaler.fit_transform(X_train)
scaler.transform(X_test)
Posted by: Guest on November-08-2020
0

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...])
Posted by: Guest on April-16-2020

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