Package weka.classifiers.meta
Class FilteredClassifier
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.meta.FilteredClassifier
- All Implemented Interfaces:
Serializable
,Cloneable
,CapabilitiesHandler
,Drawable
,OptionHandler
,RevisionHandler
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.
Valid options are:
-F <filter specification> Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Version:
- $Revision: 1.28 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz)
- See Also:
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Field Summary
Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances data) Build the classifier on the filtered data.double[]
distributionForInstance
(Instance instance) Classifies a given instance after filtering.Returns the tip text for this propertyReturns default capabilities of the classifier.Gets the filter used.String[]
Gets the current settings of the Classifier.Returns the revision string.Returns a string describing this classifiergraph()
Returns graph describing the classifier (if possible).int
Returns the type of graph this classifier represents.Returns an enumeration describing the available options.static void
Main method for testing this class.void
Sets the filtervoid
setOptions
(String[] options) Parses a given list of options.toString()
Output a representation of this classifierMethods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifier
Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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Constructor Details
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FilteredClassifier
public FilteredClassifier()Default constructor.
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Method Details
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globalInfo
Returns a string describing this classifier- Returns:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
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graphType
public int graphType()Returns the type of graph this classifier represents. -
graph
Returns graph describing the classifier (if possible). -
listOptions
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classSingleClassifierEnhancer
- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-F <filter specification> Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Specified by:
setOptions
in interfaceOptionHandler
- Overrides:
setOptions
in classSingleClassifierEnhancer
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classSingleClassifierEnhancer
- Returns:
- an array of strings suitable for passing to setOptions
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filterTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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setFilter
Sets the filter- Parameters:
filter
- the filter with all options set.
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getFilter
Gets the filter used.- Returns:
- the filter
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getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classSingleClassifierEnhancer
- Returns:
- the capabilities of this classifier
- See Also:
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buildClassifier
Build the classifier on the filtered data.- Specified by:
buildClassifier
in classClassifier
- Parameters:
data
- the training data- Throws:
Exception
- if the classifier could not be built successfully
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distributionForInstance
Classifies a given instance after filtering.- Overrides:
distributionForInstance
in classClassifier
- Parameters:
instance
- the instance to be classified- Returns:
- the class distribution for the given instance
- Throws:
Exception
- if instance could not be classified successfully
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toString
Output a representation of this classifier -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
argv
- should contain the following arguments: -t training file [-T test file] [-c class index]
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