mlpack::data::StandardScaler Class Reference

A simple Standard Scaler class. More...

#include <standard_scaler.hpp>

Public Member Functions
template<typename MatType >
void	Fit (const MatType &input)
	Function to fit features, to find out the min max and scale. More...
template<typename MatType >
void	Transform (const MatType &input, MatType &output)
	Function to scale features. More...
template<typename MatType >
void	InverseTransform (const MatType &input, MatType &output)
	Function to retrieve original dataset. More...
const arma::vec &	ItemMean () const
	Get the mean row vector.
const arma::vec &	ItemStdDev () const
	Get the standard deviation row vector.
template<typename Archive >
void	serialize (Archive &ar, const uint32_t)

Detailed Description

A simple Standard Scaler class.

Given an input dataset this class helps you to Standardize features by removing the mean and scaling to unit variance.

[z = (x - u) / s]

where u is the mean of the training samples and s is the standard deviation of the training samples.

arma::mat input;
Load("train.csv", input);
arma::mat output;

// Fit the features.
StandardScaler scale;
scale.Fit(input)

// Scale the features.
scale.Transform(input, output);

// Retransform the input.
scale.InverseTransform(output, input);

Member Function Documentation

Fit()

template<typename MatType >

void mlpack::data::StandardScaler::Fit ( const MatType &  input )

inline

Function to fit features, to find out the min max and scale.

Parameters

input

Dataset to fit.

InverseTransform()

template<typename MatType >

void mlpack::data::StandardScaler::InverseTransform ( const MatType &  input, MatType &  output  )

inline

Function to retrieve original dataset.

Parameters

input	Scaled dataset.
output	Output matrix with original Dataset.

Transform()

template<typename MatType >

void mlpack::data::StandardScaler::Transform ( const MatType &  input, MatType &  output  )

inline

Function to scale features.

Parameters

input	Dataset to scale features.
output	Output matrix with scaled features.

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The documentation for this class was generated from the following file:

• src/mlpack/core/data/scaler_methods/standard_scaler.hpp