MLLIB::MlScaler Class Reference

Feature scaler (StandardScaler or MinMaxScaler). More...

#include <ml_scaler.h>

Public Types
enum	ScalerType { StandardScaler , MinMaxScaler }

Public Member Functions
	MlScaler (ScalerType type=StandardScaler)
void	fit (const MlTensor &data)
MlTensor	transform (const MlTensor &data) const
MlTensor	fitTransform (const MlTensor &data)
MlTensor	inverseTransform (const MlTensor &data) const

Detailed Description

Feature scaler (StandardScaler or MinMaxScaler).

Definition at line 61 of file ml_scaler.h.

Member Enumeration Documentation

ScalerType

enum MLLIB::MlScaler::ScalerType

Enumerator
StandardScaler
MinMaxScaler

Definition at line 64 of file ml_scaler.h.

Constructor & Destructor Documentation

MlScaler()

MlScaler::MlScaler

(

ScalerType

type = StandardScaler

)

Construct a scaler.

Parameters

[in]

type

Scaler strategy.

Definition at line 59 of file ml_scaler.cpp.

Member Function Documentation

fit()

void MlScaler::fit

(

const MlTensor &

data

)

Compute statistics from the data.

Parameters

[in]

data

Training data (samples x features).

Definition at line 66 of file ml_scaler.cpp.

fitTransform()

MlTensor MlScaler::fitTransform

(

const MlTensor &

data

)

Convenience: fit then transform.

Parameters

[in]

data

Training data.

Returns

The scaled tensor.

Definition at line 105 of file ml_scaler.cpp.

inverseTransform()

MlTensor MlScaler::inverseTransform

(

const MlTensor &

data

)

const

Undo the scaling.

Parameters

[in]

data

Scaled data.

Returns

The original-scale tensor.

Definition at line 113 of file ml_scaler.cpp.

transform()

MlTensor MlScaler::transform

(

const MlTensor &

data

)

const

Apply the learned transform.

Parameters

[in]

data

Data to transform.

Returns

The scaled tensor.

Definition at line 86 of file ml_scaler.cpp.

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

• src/libraries/ml/ml_scaler.h
• src/libraries/ml/ml_scaler.cpp