Catalano.MachineLearning.FeatureScaling
Class MaximumNormalization
- java.lang.Object
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- Catalano.MachineLearning.FeatureScaling.MaximumNormalization
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- All Implemented Interfaces:
- IFeatureScaling, java.io.Serializable
public class MaximumNormalization extends java.lang.Object implements IFeatureScaling
Maximum Normalization. Normalize the data dividing by maximum value.- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor and Description MaximumNormalization()Initializes a new instance of the Maximum Normalization class.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description double[][]Apply(DecisionVariable[] variables, double[][] data)Apply the normalization.double[][]Apply(double[][] data)Apply the normalization.voidApplyInPlace(DecisionVariable[] attributes, double[][] data)Apply the normalization in place of the original data.voidApplyInPlace(double[][] data)Apply the normalization in place of the original data.double[]Compute(DecisionVariable[] attributes, double[] feature)Normalize the feature.double[]Compute(double[] feature)Normalize the feature.double[]getRangeNormalization()Get range normalization.voidsetRangeNormalization(double[] range)Set range normalization.
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Constructor Detail
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MaximumNormalization
public MaximumNormalization()
Initializes a new instance of the Maximum Normalization class.
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Method Detail
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getRangeNormalization
public double[] getRangeNormalization()
Get range normalization.- Returns:
- Range normalization.
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setRangeNormalization
public void setRangeNormalization(double[] range)
Set range normalization.- Parameters:
range- Range normalization.
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Apply
public double[][] Apply(double[][] data)
Description copied from interface:IFeatureScalingApply the normalization.- Specified by:
Applyin interfaceIFeatureScaling- Parameters:
data- Data to be normalized.- Returns:
- Normalized data.
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Apply
public double[][] Apply(DecisionVariable[] variables, double[][] data)
Description copied from interface:IFeatureScalingApply the normalization.- Specified by:
Applyin interfaceIFeatureScaling- Parameters:
variables- Decision variables.data- Data to be normalized.- Returns:
- Normalized. data.
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ApplyInPlace
public void ApplyInPlace(double[][] data)
Description copied from interface:IFeatureScalingApply the normalization in place of the original data.- Specified by:
ApplyInPlacein interfaceIFeatureScaling- Parameters:
data- Data to be normalized.
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ApplyInPlace
public void ApplyInPlace(DecisionVariable[] attributes, double[][] data)
Description copied from interface:IFeatureScalingApply the normalization in place of the original data.- Specified by:
ApplyInPlacein interfaceIFeatureScaling- Parameters:
attributes- Decision variables.data- Data to be normalized.
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Compute
public double[] Compute(double[] feature)
Description copied from interface:IFeatureScalingNormalize the feature.- Specified by:
Computein interfaceIFeatureScaling- Parameters:
feature- Feature to be normalized.- Returns:
- Normalized feature.
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Compute
public double[] Compute(DecisionVariable[] attributes, double[] feature)
Description copied from interface:IFeatureScalingNormalize the feature.- Specified by:
Computein interfaceIFeatureScaling- Parameters:
attributes- Decision variables.feature- Feature.- Returns:
- Normalized feature.
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