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renaming `normalizer` variable to match previously defined `norm` Normalizer
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You can also use the method below will preprocess your data separately but similar parameter used for training data set.

norm = preprocessing.Normalizer().fit(xtrain)

then

x_train_norm = normalizernorm.transform(xtrain) 
x_test_norm = normalizernorm.transform(Xtest)

You can also use the method below will preprocess your data separately but similar parameter used for training data set.

norm = preprocessing.Normalizer().fit(xtrain)

then

x_train_norm = normalizer.transform(xtrain) 
x_test_norm = normalizer.transform(Xtest)

You can also use the method below will preprocess your data separately but similar parameter used for training data set.

norm = preprocessing.Normalizer().fit(xtrain)

then

x_train_norm = norm.transform(xtrain) 
x_test_norm = norm.transform(Xtest)
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You can also use the method below will preprocess your data separately but similar parameter used for training data set.

norm = preprocessing.Normalizer().fit(xtrain)

then

x_train_norm = normalizer.transform(xtrain) 
x_test_norm = normalizer.transform(Xtest)