类 M5Base

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.m5.M5Base
所有已实现的接口:
Serializable, Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, OptionHandler, RevisionHandler, TechnicalInformationHandler
直接已知子类:
M5P, M5Rules

public abstract class M5Base extends Classifier implements AdditionalMeasureProducer, TechnicalInformationHandler
M5Base. Implements base routines for generating M5 Model trees and rules.

The original algorithm M5 was invented by Quinlan:
Quinlan J. R. (1992). Learning with continuous classes. Proceedings of the Australian Joint Conference on Artificial Intelligence. 343--348. World Scientific, Singapore.

Yong Wang made improvements and created M5':
Wang, Y and Witten, I. H. (1997). Induction of model trees for predicting continuous classes. Proceedings of the poster papers of the European Conference on Machine Learning. University of Economics, Faculty of Informatics and Statistics, Prague.

Valid options are:

-U
Use unsmoothed predictions.

-R
Build regression tree/rule rather than model tree/rule

版本:
$Revision: 6260 $
作者:
Mark Hall (mhall@cs.waikato.ac.nz)
另请参阅:
  • 构造器详细资料

    • M5Base

      public M5Base()
      Constructor
  • 方法详细资料

    • globalInfo

      public String globalInfo()
      returns information about the classifier
      返回:
      a description suitable for displaying in the explorer/experimenter gui
    • getTechnicalInformation

      public 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.
      指定者:
      getTechnicalInformation 在接口中 TechnicalInformationHandler
      返回:
      the technical information about this class
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options
      指定者:
      listOptions 在接口中 OptionHandler
      覆盖:
      listOptions 在类中 Classifier
      返回:
      an enumeration of all the available options
    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are:

      -U
      Use unsmoothed predictions.

      -R
      Build a regression tree rather than a model tree.

      指定者:
      setOptions 在接口中 OptionHandler
      覆盖:
      setOptions 在类中 Classifier
      参数:
      options - the list of options as an array of strings
      抛出:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the classifier.
      指定者:
      getOptions 在接口中 OptionHandler
      覆盖:
      getOptions 在类中 Classifier
      返回:
      an array of strings suitable for passing to setOptions
    • unprunedTipText

      public String unprunedTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setUnpruned

      public void setUnpruned(boolean unpruned)
      Use unpruned tree/rules
      参数:
      unpruned - true if unpruned tree/rules are to be generated
    • getUnpruned

      public boolean getUnpruned()
      Get whether unpruned tree/rules are being generated
      返回:
      true if unpruned tree/rules are to be generated
    • generateRulesTipText

      public String generateRulesTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • useUnsmoothedTipText

      public String useUnsmoothedTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setUseUnsmoothed

      public void setUseUnsmoothed(boolean s)
      Use unsmoothed predictions
      参数:
      s - true if unsmoothed predictions are to be used
    • getUseUnsmoothed

      public boolean getUseUnsmoothed()
      Get whether or not smoothing is being used
      返回:
      true if unsmoothed predictions are to be used
    • buildRegressionTreeTipText

      public String buildRegressionTreeTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getBuildRegressionTree

      public boolean getBuildRegressionTree()
      Get the value of regressionTree.
      返回:
      Value of regressionTree.
    • setBuildRegressionTree

      public void setBuildRegressionTree(boolean newregressionTree)
      Set the value of regressionTree.
      参数:
      newregressionTree - Value to assign to regressionTree.
    • minNumInstancesTipText

      public String minNumInstancesTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • setMinNumInstances

      public void setMinNumInstances(double minNum)
      Set the minimum number of instances to allow at a leaf node
      参数:
      minNum - the minimum number of instances
    • getMinNumInstances

      public double getMinNumInstances()
      Get the minimum number of instances to allow at a leaf node
      返回:
      a double value
    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier, i.e., of LinearRegression.
      指定者:
      getCapabilities 在接口中 CapabilitiesHandler
      覆盖:
      getCapabilities 在类中 Classifier
      返回:
      the capabilities of this classifier
      另请参阅:
    • buildClassifier

      public void buildClassifier(Instances data) throws Exception
      Generates the classifier.
      指定者:
      buildClassifier 在类中 Classifier
      参数:
      data - set of instances serving as training data
      抛出:
      Exception - if the classifier has not been generated successfully
    • classifyInstance

      public double classifyInstance(Instance inst) throws Exception
      Calculates a prediction for an instance using a set of rules or an M5 model tree
      覆盖:
      classifyInstance 在类中 Classifier
      参数:
      inst - the instance whos class value is to be predicted
      返回:
      the prediction
      抛出:
      Exception - if a prediction can't be made.
    • toString

      public String toString()
      Returns a description of the classifier
      覆盖:
      toString 在类中 Object
      返回:
      a description of the classifier as a String
    • enumerateMeasures

      public Enumeration enumerateMeasures()
      Returns an enumeration of the additional measure names
      指定者:
      enumerateMeasures 在接口中 AdditionalMeasureProducer
      返回:
      an enumeration of the measure names
    • getMeasure

      public double getMeasure(String additionalMeasureName)
      Returns the value of the named measure
      指定者:
      getMeasure 在接口中 AdditionalMeasureProducer
      参数:
      additionalMeasureName - the name of the measure to query for its value
      返回:
      the value of the named measure
      抛出:
      Exception - if the named measure is not supported
    • measureNumRules

      public double measureNumRules()
      return the number of rules
      返回:
      the number of rules (same as # linear models & # leaves in the tree)
    • getM5RootNode

      public RuleNode getM5RootNode()