Package adams.data.instancesanalysis.pls

Class PLS1

  • All Implemented Interfaces:
    adams.core.Destroyable, adams.core.GlobalInfoSupporter, adams.core.logging.LoggingLevelHandler, adams.core.logging.LoggingSupporter, adams.core.option.OptionHandler, adams.core.SizeOfHandler, adams.core.TechnicalInformationHandler, Serializable, weka.core.CapabilitiesHandler, GenericPLSMatrixAccess
    public class PLS1
extends AbstractSingleClassPLS
    Implementation of PLS1 algorithm.

    For more information see:

    Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002). A User Friendly Guide to Multivariate Calibration and Classification. NIR Publications.

    StatSoft, Inc.. Partial Least Squares (PLS).

    Bent Jorgensen, Yuri Goegebeur. Module 7: Partial least squares regression I.

    BibTeX: 
     @book{Naes2002,
    author = {Tormod Naes and Tomas Isaksson and Tom Fearn and Tony Davies},
    publisher = {NIR Publications},
    title = {A User Friendly Guide to Multivariate Calibration and Classification},
    year = {2002},
    ISBN = {0-9528666-2-5}
 }

 @misc{missing_id,
    author = {StatSoft, Inc.},
    booktitle = {Electronic Textbook StatSoft},
    title = {Partial Least Squares (PLS)},
    HTTP = {http://www.statsoft.com/textbook/stpls.html}
 }

 @misc{missing_id,
    author = {Bent Jorgensen and Yuri Goegebeur},
    booktitle = {ST02: Multivariate Data Analysis and Chemometrics},
    title = {Module 7: Partial least squares regression I},
    HTTP = {http://statmaster.sdu.dk/courses/ST02/module07/}
 }


    Valid options are: 

     -debug <value>
  If enabled, additional info may be output to the console.
  (default: false)
     -preprocessing <value>
  The type of preprocessing to perform.
  (default: CENTER)
     -C <value>
  The number of components to compute.
  (default: 20)
     -prediction <value>
  The type of prediction to perform.
  (default: NONE)
    Version:
    $Revision$
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Detail

      • m_r_hat

        protected weka.core.matrix.Matrix m_r_hat
        the regression vector "r-hat"

      • m_P

        protected weka.core.matrix.Matrix m_P
        the P matrix

      • m_W

        protected weka.core.matrix.Matrix m_W
        the W matrix

      • m_b_hat

        protected weka.core.matrix.Matrix m_b_hat
        the b-hat vector

    • Constructor Detail

      • PLS1

        public PLS1()

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing this class.
        Specified by:
        globalInfo in interface adams.core.GlobalInfoSupporter
        Specified by:
        globalInfo in class adams.core.option.AbstractOptionHandler
        Returns:
        a description of the class suitable for displaying in the explorer/experimenter gui

      • getTechnicalInformation

        public adams.core.TechnicalInformation getTechnicalInformation()
        Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
        Specified by:
        getTechnicalInformation in interface adams.core.TechnicalInformationHandler
        Specified by:
        getTechnicalInformation in class AbstractPLS
        Returns:
        the technical information about this class

      • getMatrix

        public weka.core.matrix.Matrix getMatrix​(String name)
        Returns the matrix with the specified name.
        Specified by:
        getMatrix in interface GenericPLSMatrixAccess
        Specified by:
        getMatrix in class AbstractPLS
        Parameters:
        name - the name of the matrix
        Returns:
        the matrix, null if not available

      • predict

        protected weka.core.Instances predict​(weka.core.Instances data)
        Performs predictions on the data.
        Parameters:
        data - the input data
        Returns:
        the predicted data

      • doTransform

        protected weka.core.Instances doTransform​(weka.core.Instances data,
                                          Map<String,​Object> params)
                                   throws Exception
        Transforms the data, initializes if necessary.
        Specified by:
        doTransform in class AbstractPLS
        Parameters:
        data - the data to use
        params - additional parameters
        Returns:
        the transformed data
        Throws:
        Exception