jsat.datatransform
Class WhitenedZCA
- java.lang.Object
-
- jsat.datatransform.DataTransformBase
-
- jsat.datatransform.WhitenedPCA
-
- jsat.datatransform.WhitenedZCA
-
- All Implemented Interfaces:
- java.io.Serializable, java.lang.Cloneable, DataTransform, InPlaceTransform, Parameterized
public class WhitenedZCA extends WhitenedPCA implements InPlaceTransform
An extension ofWhitenedPCA, is the Whitened Zero Component Analysis. Whitened ZCA can not project to a lower dimension, as it rotates the output in the original dimension.- See Also:
- Serialized Form
-
-
Constructor Summary
Constructors Constructor and Description WhitenedZCA()Creates a new WhitenedZCA transform that uses up to 50 dimensions for the transformed space.WhitenedZCA(DataSet dataSet)Creates a new Whitened ZCA transform from the given data.WhitenedZCA(DataSet dataSet, double regularization)Creates a new Whitened ZCA transform from the given data.WhitenedZCA(double regularization, int dims)Creates a new WhitenedZCA transformWhitenedZCA(int dims)Creates a new WhitenedZCA transform
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description voidfit(DataSet dataSet)Fits this transform to the given dataset.voidmutableTransform(DataPoint dp)Mutates the given data point.booleanmutatesNominal()By default returnsfalse.-
Methods inherited from class jsat.datatransform.WhitenedPCA
clone, getDimensions, getRegularization, guessDimensions, setDimensions, setRegularization, transform
-
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Methods inherited from interface jsat.datatransform.DataTransform
clone, transform
-
Methods inherited from interface jsat.parameters.Parameterized
getParameter, getParameters
-
-
-
-
Constructor Detail
-
WhitenedZCA
public WhitenedZCA()
Creates a new WhitenedZCA transform that uses up to 50 dimensions for the transformed space. This may not be optimal for any given dataset.- Parameters:
dims- the number of dimensions to project down to
-
WhitenedZCA
public WhitenedZCA(int dims)
Creates a new WhitenedZCA transform- Parameters:
dims- the number of dimensions to project down to
-
WhitenedZCA
public WhitenedZCA(double regularization, int dims)Creates a new WhitenedZCA transform- Parameters:
regularization- the amount of regularization to add, avoids numerical instabilitydims- the number of dimensions to project down to
-
WhitenedZCA
public WhitenedZCA(DataSet dataSet, double regularization)
Creates a new Whitened ZCA transform from the given data.- Parameters:
dataSet- the data set to whitenregularization- the amount of regularization to add, avoids numerical instability
-
WhitenedZCA
public WhitenedZCA(DataSet dataSet)
Creates a new Whitened ZCA transform from the given data. The regularization parameter will be chosen as the log of the condition of the covariance.- Parameters:
dataSet- the data set to whiten
-
-
Method Detail
-
fit
public void fit(DataSet dataSet)
Description copied from interface:DataTransformFits this transform to the given dataset. Some transforms can only be learned from classification or regression datasets. If an incompatible dataset type is given, aFailedToFitExceptionexception may be thrown.- Specified by:
fitin interfaceDataTransform- Overrides:
fitin classWhitenedPCA- Parameters:
dataSet- the dataset to fir this transform to
-
mutableTransform
public void mutableTransform(DataPoint dp)
Description copied from interface:InPlaceTransformMutates the given data point. This causes side effects, altering the data point to have the same value as the output ofDataTransform.transform(jsat.classifiers.DataPoint).- Specified by:
mutableTransformin interfaceInPlaceTransform- Parameters:
dp- the data point to alter
-
mutatesNominal
public boolean mutatesNominal()
Description copied from interface:InPlaceTransformBy default returnsfalse. Only returns true if this transform will mutableTransform the nominal feature values of a data point.- Specified by:
mutatesNominalin interfaceInPlaceTransform- Returns:
trueif nominal feature values are mutated,falseotherwise.
-
-
DataMelt 3.0 © DataMelt by jWork.ORG