Package deepnetts.data.norm

Class Standardizer

java.lang.Object

deepnetts.data.norm.AbstractScaler

deepnetts.data.norm.Standardizer

All Implemented Interfaces:

Serializable, javax.visrec.ml.data.preprocessing.Scaler<javax.visrec.ml.data.DataSet<MLDataItem>>

public class Standardizer
extends AbstractScaler

Performs standardization on inputs in order to get desired statistical properties of the data set (zero mean and one standard deviation). X = (X - MEAN) / STD

Author:

Zoran Sevarac

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
Standardizer(javax.visrec.ml.data.DataSet<MLDataItem> dataSet)

Method Summary

Modifier and Type	Method	Description
void	apply(javax.visrec.ml.data.DataSet<MLDataItem> dataSet)
void	scaleInput(TensorBase input)	Normalize input of deployed model

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

Standardizer

public Standardizer(javax.visrec.ml.data.DataSet<MLDataItem> dataSet)

Method Details

apply

public void apply(javax.visrec.ml.data.DataSet<MLDataItem> dataSet)

scaleInput

public void scaleInput(TensorBase input)

Description copied from class: AbstractScaler

Normalize input of deployed model

Specified by:

scaleInput in class AbstractScaler

Parameters:

input -