类 M5P
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.m5.M5Base
weka.classifiers.trees.M5P
- 所有已实现的接口:
Serializable
,Cloneable
,AdditionalMeasureProducer
,CapabilitiesHandler
,Drawable
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
M5Base. Implements base routines for generating M5 Model trees and rules
The original algorithm M5 was invented by R. Quinlan and Yong Wang made improvements.
For more information see:
Ross J. Quinlan: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence, Singapore, 343-348, 1992.
Y. Wang, I. H. Witten: Induction of model trees for predicting continuous classes. In: Poster papers of the 9th European Conference on Machine Learning, 1997. BibTeX:
The original algorithm M5 was invented by R. Quinlan and Yong Wang made improvements.
For more information see:
Ross J. Quinlan: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence, Singapore, 343-348, 1992.
Y. Wang, I. H. Witten: Induction of model trees for predicting continuous classes. In: Poster papers of the 9th European Conference on Machine Learning, 1997. BibTeX:
@inproceedings{Quinlan1992, address = {Singapore}, author = {Ross J. Quinlan}, booktitle = {5th Australian Joint Conference on Artificial Intelligence}, pages = {343-348}, publisher = {World Scientific}, title = {Learning with Continuous Classes}, year = {1992} } @inproceedings{Wang1997, author = {Y. Wang and I. H. Witten}, booktitle = {Poster papers of the 9th European Conference on Machine Learning}, publisher = {Springer}, title = {Induction of model trees for predicting continuous classes}, year = {1997} }Valid options are:
-N Use unpruned tree/rules
-U Use unsmoothed predictions
-R Build regression tree/rule rather than a model tree/rule
-M <minimum number of instances> Set minimum number of instances per leaf (default 4)
-L Save instances at the nodes in the tree (for visualization purposes)
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字段概要
从接口继承的字段 weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
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构造器概要
构造器 -
方法概要
修饰符和类型方法说明String[]
Gets the current settings of the classifier.Returns the revision string.boolean
Get whether instance data is being save.graph()
Return a dot style String describing the tree.int
Returns the type of graph this classifier represents.Returns an enumeration describing the available optionsstatic void
Main method by which this class can be testedReturns the tip text for this propertyvoid
setOptions
(String[] options) Parses a given list of options.void
setSaveInstances
(boolean save) Set whether to save instance data at each node in the tree for visualization purposes从类继承的方法 weka.classifiers.trees.m5.M5Base
buildClassifier, buildRegressionTreeTipText, classifyInstance, enumerateMeasures, generateRulesTipText, getBuildRegressionTree, getCapabilities, getM5RootNode, getMeasure, getMinNumInstances, getTechnicalInformation, getUnpruned, getUseUnsmoothed, globalInfo, measureNumRules, minNumInstancesTipText, setBuildRegressionTree, setMinNumInstances, setUnpruned, setUseUnsmoothed, toString, unprunedTipText, useUnsmoothedTipText
从类继承的方法 weka.classifiers.Classifier
debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug
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构造器详细资料
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M5P
public M5P()Creates a newM5P
instance.
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方法详细资料
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graphType
public int graphType()Returns the type of graph this classifier represents. -
graph
Return a dot style String describing the tree. -
saveInstancesTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setSaveInstances
public void setSaveInstances(boolean save) Set whether to save instance data at each node in the tree for visualization purposes- 参数:
save
- aboolean
value
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getSaveInstances
public boolean getSaveInstances()Get whether instance data is being save.- 返回:
- a
boolean
value
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listOptions
Returns an enumeration describing the available options- 指定者:
listOptions
在接口中OptionHandler
- 覆盖:
listOptions
在类中M5Base
- 返回:
- an enumeration of all the available options
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setOptions
Parses a given list of options. Valid options are:-N Use unpruned tree/rules
-U Use unsmoothed predictions
-R Build regression tree/rule rather than a model tree/rule
-M <minimum number of instances> Set minimum number of instances per leaf (default 4)
-L Save instances at the nodes in the tree (for visualization purposes)
- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中M5Base
- 参数:
options
- the list of options as an array of strings- 抛出:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the classifier.- 指定者:
getOptions
在接口中OptionHandler
- 覆盖:
getOptions
在类中M5Base
- 返回:
- an array of strings suitable for passing to setOptions
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getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中Classifier
- 返回:
- the revision
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main
Main method by which this class can be tested- 参数:
args
- an array of options
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