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API Documentation
scaler
Category: Data Processing
Classes
Scaler (BaseEstimator, TransformerMixin)
Extension of Scikit-learn's StandardScaler which allows scaling by different powers of the standard deviation.
Methods
init(scale_power, copy, with_mean, with_std)
fit(X, y)
Compute the mean and standard deviation from a dataset to use in future scaling operations.
partial_fit(X, y)
Performs online computation of mean and standard deviation on X for later scaling.
All of X is processed as a single batch.
This is intended for cases when fit is
not feasible due to very large number of n_samples
or because X is read from a continuous stream.
transform(X, y, copy)
Perform standardization by centering and scaling using the parameters.
inverse_transform(X, copy)
Scale back the data to the original representation.