PYTHON

normalize data python

from sklearn import preprocessing

data = [[ 1., -1.,  2.],
        [ 2.,  0.,  0.],
        [ 0.,  1., -1.]]
normalize(data)

# produces
array([[ 0.40824829, -0.40824829,  0.81649658],
       [ 1.        ,  0.        ,  0.        ],
       [ 0.        ,  0.70710678, -0.70710678]])

data normalization python

from sklearn import preprocessing
normalizer = preprocessing.Normalizer().fit(X_train)  
X_train = normalizer.transform(X_train)
X_test = normalizer.transform(X_test)

what is data normalization

Method to normalize data so that data redundency is reduced