weka.classifiers.misc

Class InputMappedClassifier

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

weka.classifiers.misc.InputMappedClassifier

All Implemented Interfaces:

Serializable, Cloneable, Classifier, AdditionalMeasureProducer, CapabilitiesHandler, Drawable, EnvironmentHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler

public class InputMappedClassifier
extends SingleClassifierEnhancer
implements Serializable, OptionHandler, Drawable, WeightedInstancesHandler, AdditionalMeasureProducer, EnvironmentHandler

Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure. Model attributes that are not found in the incoming instances receive missing values, so do incoming nominal attribute values that the classifier has not seen before. A new classifier can be trained or an existing one loaded from a file.

Valid options are:

 -I
  Ignore case when matching attribute names and nominal values.
 

 -M
  Suppress the output of the mapping report.
 

 -trim
  Trim white space from either end of names before matching.
 

 -L <path to model to load>
  Path to a model to load. If set, this model
  will be used for prediction and any base classifier
  specification will be ignored. Environment variables
  may be used in the path (e.g. ${HOME}/myModel.model)
 

 -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.rules.ZeroR)
 

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 

Version:

$Revision: 10153 $

Author:

Mark Hall (mhall{[at]}pentaho{[dot]}com)

See Also:

Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
InputMappedClassifier()

Method Summary

Methods

Modifier and Type	Method and Description
void	buildClassifier(Instances data) Build the classifier
double	classifyInstance(Instance inst) Classifies the given test instance.
Instance	constructMappedInstance(Instance incoming)
double[]	distributionForInstance(Instance inst) Predicts the class memberships for a given instance.
Enumeration<String>	enumerateMeasures() Returns an enumeration of the additional measure names
Capabilities	getCapabilities() Returns default capabilities of the classifier.
boolean	getIgnoreCaseForNames() Get whether to ignore case when matching attribute names and nominal values.
int	getMappedClassIndex()
double	getMeasure(String additionalMeasureName) Returns the value of the named measure
Instances	getModelHeader(Instances defaultH) Return the instance structure that the encapsulated model was built with.
String	getModelPath() Get the path used for loading a model.
String[]	getOptions() Gets the current settings of the Classifier.
String	getRevision() Returns the revision string.
boolean	getSuppressMappingReport() Get whether to suppress output the report of model to input mappings.
boolean	getTrim() Get whether to trim white space from each end of names before matching.
String	globalInfo() Returns a string describing this classifier
String	graph() Returns graph describing the classifier (if possible).
int	graphType() Returns the type of graph this classifier represents.
String	ignoreCaseForNamesTipText() Returns the tip text for this property
Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	modelPathTipText() Returns the tip text for this property
void	setEnvironment(Environment env) Set the environment variables to use
void	setIgnoreCaseForNames(boolean ignore) Set whether to ignore case when matching attribute names and nominal values.
void	setModelHeader(Instances modelHeader) Set the structure of the data used to create the model.
void	setModelPath(String modelPath) Set the path from which to load a model.
void	setOptions(String[] options) Parses a given list of options.
void	setSuppressMappingReport(boolean suppress) Set whether to suppress output the report of model to input mappings.
void	setTestStructure(Instances testStructure) Set the test structure (if known in advance) that we are likely to see.
void	setTrim(boolean trim) Set whether to trim white space from each end of names before matching.
String	suppressMappingReportTipText() Returns the tip text for this property
String	toString()
String	trimTipText() Returns the tip text for this property

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

InputMappedClassifier

public InputMappedClassifier()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

setEnvironment

public void setEnvironment(Environment env)

Set the environment variables to use

Specified by:

setEnvironment in interface EnvironmentHandler

Parameters:

env - the environment variables to use

ignoreCaseForNamesTipText

public String ignoreCaseForNamesTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setIgnoreCaseForNames

public void setIgnoreCaseForNames(boolean ignore)

Set whether to ignore case when matching attribute names and nominal values.

Parameters:

ignore - true if case is to be ignored

getIgnoreCaseForNames

public boolean getIgnoreCaseForNames()

Get whether to ignore case when matching attribute names and nominal values.

Returns:

true if case is to be ignored.

trimTipText

public String trimTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setTrim

public void setTrim(boolean trim)

Set whether to trim white space from each end of names before matching.

Parameters:

trim - true to trim white space.

getTrim

public boolean getTrim()

Get whether to trim white space from each end of names before matching.

Returns:

true if white space is to be trimmed.

suppressMappingReportTipText

public String suppressMappingReportTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setSuppressMappingReport

public void setSuppressMappingReport(boolean suppress)

Set whether to suppress output the report of model to input mappings.

Parameters:

suppress - true to suppress this output.

getSuppressMappingReport

public boolean getSuppressMappingReport()

Get whether to suppress output the report of model to input mappings.

Returns:

true if this output is to be suppressed.

modelPathTipText

public String modelPathTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

setModelPath

public void setModelPath(String modelPath)
                  throws Exception

Set the path from which to load a model. Loading occurs when the first test instance is received or getModelHeader() is called programatically. Environment variables can be used in the supplied path - e.g. ${HOME}/myModel.model.

Parameters:

modelPath - the path to the model to load.

Throws:

Exception - if a problem occurs during loading.

getModelPath

public String getModelPath()

Get the path used for loading a model.

Returns:

the path used for loading a model.

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface Classifier

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class SingleClassifierEnhancer

Returns:

the capabilities of this classifier

See Also:

Capabilities

listOptions

public Enumeration<Option> listOptions()

Returns an enumeration describing the available options. Valid options are:

 -I
  Ignore case when matching attribute names and nominal values.
 

 -M
  Suppress the output of the mapping report.
 

 -trim
  Trim white space from either end of names before matching.
 

 -L <path to model to load>
  Path to a model to load. If set, this model
  will be used for prediction and any base classifier
  specification will be ignored. Environment variables
  may be used in the path (e.g. ${HOME}/myModel.model)
 

 -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.rules.ZeroR)
 

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class SingleClassifierEnhancer

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -I
  Ignore case when matching attribute names and nominal values.
 

 -M
  Suppress the output of the mapping report.
 

 -trim
  Trim white space from either end of names before matching.
 

 -L <path to model to load>
  Path to a model to load. If set, this model
  will be used for prediction and any base classifier
  specification will be ignored. Environment variables
  may be used in the path (e.g. ${HOME}/myModel.model)
 

 -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.rules.ZeroR)
 

 Options specific to classifier weka.classifiers.rules.ZeroR:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console
 

Options after -- are passed to the designated classifier.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class SingleClassifierEnhancer

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class SingleClassifierEnhancer

Returns:

an array of strings suitable for passing to setOptions

setTestStructure

public void setTestStructure(Instances testStructure)

Set the test structure (if known in advance) that we are likely to see. If set, then a call to buildClassifier() will not overwrite any test structure that has been recorded with the current training structure. This is useful for getting a correct mapping report output in toString() after buildClassifier has been called and before any test instance has been seen. Test structure and mapping will get reset if a test instance is received whose structure does not match the recorded test structure.

Parameters:

testStructure - the structure of the test instances that we are likely to see (if known in advance)

setModelHeader

public void setModelHeader(Instances modelHeader)

Set the structure of the data used to create the model. This method is useful for clients who have an existing in-memory model that they'd like to wrap in the InputMappedClassifier

Parameters:

modelHeader - the structure of the data used to build the wrapped model

buildClassifier

public void buildClassifier(Instances data)
                     throws Exception

Build the classifier

Specified by:

buildClassifier in interface Classifier

Parameters:

data - the training data to be used for generating the bagged classifier.

Throws:

Exception - if the classifier could not be built successfully

getModelHeader

public Instances getModelHeader(Instances defaultH)
                         throws Exception

Return the instance structure that the encapsulated model was built with. If the classifier will be built from scratch by InputMappedClassifier then this method just returns the default structure that is passed in as argument.

Parameters:

defaultH - the default instances structure

Returns:

the instances structure used to create the encapsulated model

Throws:

Exception - if a problem occurs

getMappedClassIndex

public int getMappedClassIndex()
                        throws Exception

Throws:

Exception

constructMappedInstance

public Instance constructMappedInstance(Instance incoming)
                                 throws Exception

Throws:

Exception

classifyInstance

public double classifyInstance(Instance inst)
                        throws Exception

Description copied from class: AbstractClassifier

Classifies the given test instance. The instance has to belong to a dataset when it's being classified. Note that a classifier MUST implement either this or distributionForInstance().

Specified by:

classifyInstance in interface Classifier

Overrides:

classifyInstance in class AbstractClassifier

Parameters:

inst - the instance to be classified

Returns:

the predicted most likely class for the instance or Utils.missingValue() if no prediction is made

Throws:

Exception - if an error occurred during the prediction

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws Exception

Description copied from class: AbstractClassifier

Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero. If the class is numeric, the array must consist of only one element, which contains the predicted value. Note that a classifier MUST implement either this or classifyInstance().

Specified by:

distributionForInstance in interface Classifier

Overrides:

distributionForInstance in class AbstractClassifier

Parameters:

inst - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction

Throws:

Exception - if distribution could not be computed successfully

toString

public String toString()

Overrides:

toString in class Object

graphType

public int graphType()

Returns the type of graph this classifier represents.

Specified by:

graphType in interface Drawable

Returns:

the type of graph

enumerateMeasures

public Enumeration<String> enumerateMeasures()

Returns an enumeration of the additional measure names

Specified by:

enumerateMeasures in interface AdditionalMeasureProducer

Returns:

an enumeration of the measure names

getMeasure

public double getMeasure(String additionalMeasureName)

Returns the value of the named measure

Specified by:

getMeasure in interface AdditionalMeasureProducer

Parameters:

additionalMeasureName - the name of the measure to query for its value

Returns:

the value of the named measure

Throws:

IllegalArgumentException - if the named measure is not supported

graph

public String graph()
             throws Exception

Returns graph describing the classifier (if possible).

Specified by:

graph in interface Drawable

Returns:

the graph of the classifier in dotty format

Throws:

Exception - if the classifier cannot be graphed

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]