Uses of Class
adams.data.instancesanalysis.pls.AbstractPLS

Packages that use AbstractPLS

Package	Description
adams.data.instancesanalysis
adams.data.instancesanalysis.pls
weka.classifiers.functions
weka.filters.supervised.attribute

Uses of AbstractPLS in adams.data.instancesanalysis

Fields in adams.data.instancesanalysis declared as AbstractPLS

Modifier and Type	Field	Description
protected AbstractPLS	PLS.m_Algorithm	the algorithm to use.

Methods in adams.data.instancesanalysis that return AbstractPLS

Modifier and Type	Method	Description
AbstractPLS	PLS.getAlgorithm()	Returns the algorithm to use.

Methods in adams.data.instancesanalysis with parameters of type AbstractPLS

Modifier and Type	Method	Description
void	PLS.setAlgorithm(AbstractPLS value)	Sets the algorithm to use.

Uses of AbstractPLS in adams.data.instancesanalysis.pls

Subclasses of AbstractPLS in adams.data.instancesanalysis.pls

Modifier and Type	Class	Description
class	AbstractMultiClassPLS	Ancestor for schemes that predict multiple classes.
class	AbstractSingleClassPLS	Ancestor for schemes that predict a single class.
class	DIPLS	Domain Invariant Partial Least Squares (DIPLS). For more information see: Ramin Nikzad-Langerodi, Werner Zellinger, Edwin Lughofer,, Susanne Saminger-Platz.
class	KernelPLS	Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space For more information see: Roman Rosipal, Leonard J.
class	NIPALS	Nonlinear Iterative Partial Least Squares (NIPALS). For more information see: scikit-learn.
class	OPLS	Orthogonal Projections to latent structures (O-PLS). For more informatio see: Johan Trygg, Svante Wold (2001).
class	PLS1	Implementation of PLS1 algorithm. For more information see: Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).
class	PRM	Partial robust M-regression (PRM). For more information see: Sven Serneels, Christophe Croux, Peter Filzmoser, Pierre J.Van Espen (2005).
class	SIMPLS	Implementation of SIMPLS algorithm. Available matrices: W, B For more information see: Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).
class	SparsePLS	Nonlinear Iterative Partial Least Squares (SparsePLS). Automatically standardizes X and Y internally. For more information see: Chun H, Keles S. (2010).
class	VCPLS	Variance constrained partial least squares. For more information see: Xiubao Jiang, Xinge You, Shujian Yu, Dacheng Tao, C.L.

Uses of AbstractPLS in weka.classifiers.functions

Fields in weka.classifiers.functions declared as AbstractPLS

Modifier and Type	Field	Description
protected AbstractPLS	PLSRegressor.m_Algorithm	the PLS algorithm
protected AbstractPLS	PLSWeighted.m_Algorithm	the PLS algorithm

Methods in weka.classifiers.functions that return AbstractPLS

Modifier and Type	Method	Description
AbstractPLS	PLSRegressor.getAlgorithm()	Returns the PLS algorithm to use.
AbstractPLS	PLSWeighted.getAlgorithm()	Get the PLS algorithm.
protected AbstractPLS	PLSRegressor.getDefaultAlgorithm()	Returns the default algorithm.
AbstractPLS	PLSWeighted.getDefaultAlgorithm()	Returns the default PLS filter.

Methods in weka.classifiers.functions with parameters of type AbstractPLS

Modifier and Type	Method	Description
void	PLSRegressor.setAlgorithm(AbstractPLS value)	Sets the PLS algorithm to use.
void	PLSWeighted.setAlgorithm(AbstractPLS value)	Set the PLS algorithm (only used for setup).

Uses of AbstractPLS in weka.filters.supervised.attribute

Fields in weka.filters.supervised.attribute declared as AbstractPLS

Modifier and Type	Field	Description
protected AbstractPLS	MultiPLS.m_Algorithm	the PLS algorithm.
protected AbstractPLS	PLS.m_Algorithm	the PLS algorithm.

Fields in weka.filters.supervised.attribute with type parameters of type AbstractPLS

Modifier and Type	Field	Description
protected Map<String,AbstractPLS>	MultiPLS.m_PLS	the PLS algorithms corresponding to the Y attributes.

Methods in weka.filters.supervised.attribute that return AbstractPLS

Modifier and Type	Method	Description
AbstractPLS	MultiPLS.getAlgorithm()	Returns the PLS algorithm to use.
AbstractPLS	PLS.getAlgorithm()	Returns the PLS algorithm to use.
protected AbstractPLS	MultiPLS.getDefaultAlgorithm()	Returns the default algorithm.
protected AbstractPLS	PLS.getDefaultAlgorithm()	Returns the default algorithm.

Methods in weka.filters.supervised.attribute with parameters of type AbstractPLS

Modifier and Type	Method	Description
void	MultiPLS.setAlgorithm(AbstractPLS value)	Sets the PLS algorithm to use.
void	PLS.setAlgorithm(AbstractPLS value)	Sets the PLS algorithm to use.