Preprocessing

Transform Classes

preprocessing.LabelBinarizer(*[, neg_label, ...])	Binarize labels in a one-vs-all fashion.
preprocessing.LabelEncoder()	Encode target labels with value between 0 and n_classes-1.
preprocessing.MinMaxScaler([feature_range, ...])	Transform features by scaling each feature to a given range.
preprocessing.StandardScaler(*[, copy, ...])	Standardize features by removing the mean and scaling to unit variance.

Transform Functions

preprocessing.label_binarize(y, *, classes)	Binarize labels in a one-vs-all fashion.
preprocessing.minmax_scale(X[, ...])	Transform features by scaling each feature to a given range.
preprocessing.normalize(X[, norm, axis, ...])	Scale input vectors individually to unit norm (vector length).
preprocessing.scale(X, *[, axis, with_mean, ...])	Standardize a dataset along any axis.