Package weka.filters.supervised.attribute

Class PLSFilterWithLoadings

  • All Implemented Interfaces:
    Serializable, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, PLSMatrixAccess, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.filters.SupervisedFilter
    public class PLSFilterWithLoadings
extends weka.filters.supervised.attribute.PLSFilter
implements PLSMatrixAccess
    Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
    By default it replaces missing values and centers the data.

    Allows access to the internal matrices.

    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.

    S. de Jong (1993). SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems. 18:251-263.

    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/}
 }
 
 @article{Jong1993,
    author = {S. de Jong},
    journal = {Chemometrics and Intelligent Laboratory Systems},
    pages = {251-263},
    title = {SIMPLS: an alternative approach to partial least squares regression},
    volume = {18},
    year = {1993}
 }


    Valid options are: 

     -D
  Turns on output of debugging information.
     -C <num>
  The number of components to compute.
  (default: 20)
     -U
  Updates the class attribute as well.
  (default: off)
     -M
  Turns replacing of missing values on.
  (default: off)
     -A <SIMPLS|PLS1>
  The algorithm to use.
  (default: PLS1)
     -P <none|center|standardize>
  The type of preprocessing that is applied to the data.
  (default: center)
    Version:
    $Revision$
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Summary

      • Fields inherited from class weka.filters.supervised.attribute.PLSFilter

        ALGORITHM_PLS1, ALGORITHM_SIMPLS, m_Algorithm, m_ClassMean, m_ClassStdDev, m_Filter, m_Missing, m_NumComponents, m_PerformPrediction, m_PLS1_b_hat, m_PLS1_P, m_PLS1_RegVector, m_PLS1_W, m_Preprocessing, m_ReplaceMissing, m_SIMPLS_B, m_SIMPLS_W, PREPROCESSING_CENTER, PREPROCESSING_NONE, PREPROCESSING_STANDARDIZE, TAGS_ALGORITHM, TAGS_PREPROCESSING

      • Fields inherited from class weka.filters.Filter

        m_Debug, m_DoNotCheckCapabilities, m_FirstBatchDone, m_InputRelAtts, m_InputStringAtts, m_NewBatch, m_OutputRelAtts, m_OutputStringAtts

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      weka.core.matrix.Matrix getPLS1bHat()
      Returns the PLS1 b "hat" matrix.
      weka.core.matrix.Matrix getPLS1P()
      Returns the PLS1 P matrix.
      weka.core.matrix.Matrix getPLS1RegVector()
      Returns the reg vector.
      weka.core.matrix.Matrix getPLS1W()
      Returns the PLS1 W matrix.
      String getRevision()
      Returns the revision string.
      weka.core.matrix.Matrix getSimplsB()
      Returns the SIMPLS B matrix.
      weka.core.matrix.Matrix getSimplsW()
      Returns the SIMPLS W matrix.
      String globalInfo()
      Returns a string describing this classifier.
      static void main​(String[] args)
      runs the filter with the given arguments.

      • Methods inherited from class weka.filters.supervised.attribute.PLSFilter

        algorithmTipText, columnAsVector, determineOutputFormat, getAlgorithm, getCapabilities, getDominantEigenVector, getNumComponents, getOptions, getPerformPrediction, getPreprocessing, getReplaceMissing, getTechnicalInformation, getVector, getX, getX, getY, getY, listOptions, normalizeVector, numComponentsTipText, performPredictionTipText, preprocessingTipText, process, processPLS1, processSIMPLS, replaceMissingTipText, setAlgorithm, setNumComponents, setOptions, setPerformPrediction, setPreprocessing, setReplaceMissing, setVector, toInstances

      • Methods inherited from class weka.filters.SimpleBatchFilter

        allowAccessToFullInputFormat, batchFinished, hasImmediateOutputFormat, input, input

      • Methods inherited from class weka.filters.SimpleFilter

        reset, setInputFormat

      • Methods inherited from class weka.filters.Filter

        batchFilterFile, bufferInput, copyValues, copyValues, debugTipText, doNotCheckCapabilitiesTipText, filterFile, flushInput, getCapabilities, getCopyOfInputFormat, getDebug, getDoNotCheckCapabilities, getInputFormat, getOutputFormat, initInputLocators, initOutputLocators, inputFormatPeek, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, mayRemoveInstanceAfterFirstBatchDone, numPendingOutput, output, outputFormatPeek, outputPeek, postExecution, preExecution, push, push, resetQueue, run, runFilter, setDebug, setDoNotCheckCapabilities, setOutputFormat, testInputFormat, toString, useFilter, wekaStaticWrapper

    • Constructor Detail

      • PLSFilterWithLoadings

        public PLSFilterWithLoadings()

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing this classifier.
        Overrides:
        globalInfo in class weka.filters.supervised.attribute.PLSFilter
        Returns:
        a description of the classifier suitable for displaying in the explorer/experimenter gui

      • getPLS1RegVector

        public weka.core.matrix.Matrix getPLS1RegVector()
        Returns the reg vector.
        Specified by:
        getPLS1RegVector in interface PLSMatrixAccess
        Returns:
        the vector

      • getPLS1P

        public weka.core.matrix.Matrix getPLS1P()
        Returns the PLS1 P matrix.
        Specified by:
        getPLS1P in interface PLSMatrixAccess
        Returns:
        the matrix

      • getPLS1W

        public weka.core.matrix.Matrix getPLS1W()
        Returns the PLS1 W matrix.
        Specified by:
        getPLS1W in interface PLSMatrixAccess
        Returns:
        the matrix

      • getPLS1bHat

        public weka.core.matrix.Matrix getPLS1bHat()
        Returns the PLS1 b "hat" matrix.
        Specified by:
        getPLS1bHat in interface PLSMatrixAccess
        Returns:
        the matrix

      • getSimplsW

        public weka.core.matrix.Matrix getSimplsW()
        Returns the SIMPLS W matrix.
        Specified by:
        getSimplsW in interface PLSMatrixAccess
        Returns:
        the matrix

      • getSimplsB

        public weka.core.matrix.Matrix getSimplsB()
        Returns the SIMPLS B matrix.
        Specified by:
        getSimplsB in interface PLSMatrixAccess
        Returns:
        the matrix

      • getRevision

        public String getRevision()
        Returns the revision string.
        Specified by:
        getRevision in interface weka.core.RevisionHandler
        Overrides:
        getRevision in class weka.filters.supervised.attribute.PLSFilter
        Returns:
        the revision

      • main

        public static void main​(String[] args)
        runs the filter with the given arguments.
        Parameters:
        args - the commandline arguments