InputMappedClassifier

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.SingleClassifierEnhancer
  - - weka.classifiers.misc.InputMappedClassifier

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, Classifier, AdditionalMeasureProducer, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, Drawable, EnvironmentHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler

public class InputMappedClassifier
extends SingleClassifierEnhancer
implements java.io.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: 15211 $
Author:: Mark Hall (mhall{[at]}pentaho{[dot]}com)
See Also:: Serialized Form

Field Summary
- Fields inherited from class weka.classifiers.AbstractClassifier
  BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT
- Fields inherited from interface weka.core.Drawable
  BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors
Constructor and Description

InputMappedClassifier()

Constructors
Constructor and Description
`InputMappedClassifier()`

Method Summary

All Methods Static Methods Instance Methods Concrete 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.
`java.util.Enumeration<java.lang.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(java.lang.String additionalMeasureName)` Returns the value of the named measure
`Instances`	`getModelHeader(Instances defaultH)` Return the instance structure that the encapsulated model was built with.
`java.lang.String`	`getModelPath()` Get the path used for loading a model.
`java.lang.String[]`	`getOptions()` Gets the current settings of the Classifier.
`java.lang.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.
`java.lang.String`	`globalInfo()` Returns a string describing this classifier
`java.lang.String`	`graph()` Returns graph describing the classifier (if possible).
`int`	`graphType()` Returns the type of graph this classifier represents.
`java.lang.String`	`ignoreCaseForNamesTipText()` Returns the tip text for this property
`java.util.Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.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(java.lang.String modelPath)` Set the path from which to load a model.
`void`	`setOptions(java.lang.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.
`java.lang.String`	`suppressMappingReportTipText()` Returns the tip text for this property
`java.lang.String`	`toString()`
`java.lang.String`	`trimTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, postExecution, preExecution, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - InputMappedClassifier
```
public InputMappedClassifier()
```
- Method Detail
  - globalInfo
```
public java.lang.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 java.lang.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 java.lang.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 java.lang.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 java.lang.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(java.lang.String modelPath)
                  throws java.lang.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:
    
    java.lang.Exception - if a problem occurs during loading.
  - getModelPath
```
public java.lang.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 java.util.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(java.lang.String[] options)
                throws java.lang.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:
    
    java.lang.Exception - if an option is not supported
  - getOptions
```
public java.lang.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 java.lang.Exception
```
    Build the classifier
    
    Specified by:
    
    buildClassifier in interface Classifier
    
    Parameters:
    
    data - the training data to be used for generating the bagged classifier.
    
    Throws:
    
    java.lang.Exception - if the classifier could not be built successfully
  - getModelHeader
```
public Instances getModelHeader(Instances defaultH)
                         throws java.lang.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:
    
    java.lang.Exception - if a problem occurs
  - getMappedClassIndex
```
public int getMappedClassIndex()
                        throws java.lang.Exception
```
    Throws:
    
    java.lang.Exception
  - constructMappedInstance
```
public Instance constructMappedInstance(Instance incoming)
                                 throws java.lang.Exception
```
    Throws:
    
    java.lang.Exception
  - classifyInstance
```
public double classifyInstance(Instance inst)
                        throws java.lang.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:
    
    java.lang.Exception - if an error occurred during the prediction
  - distributionForInstance
```
public double[] distributionForInstance(Instance inst)
                                 throws java.lang.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:
    
    java.lang.Exception - if distribution could not be computed successfully
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.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 java.util.Enumeration<java.lang.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(java.lang.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:
    
    java.lang.IllegalArgumentException - if the named measure is not supported
  - graph
```
public java.lang.String graph()
                       throws java.lang.Exception
```
    Returns graph describing the classifier (if possible).
    
    Specified by:
    
    graph in interface Drawable
    
    Returns:
    
    the graph of the classifier in dotty format
    
    Throws:
    
    java.lang.Exception - if the classifier cannot be graphed
  - getRevision
```
public java.lang.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(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain the following arguments: -t training file [-T test file] [-c class index]

Class InputMappedClassifier

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

Fields inherited from interface weka.core.Drawable

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

InputMappedClassifier

Method Detail

globalInfo

setEnvironment

ignoreCaseForNamesTipText

setIgnoreCaseForNames

getIgnoreCaseForNames

trimTipText

setTrim

getTrim

suppressMappingReportTipText

setSuppressMappingReport

getSuppressMappingReport

modelPathTipText

setModelPath

getModelPath

getCapabilities

listOptions

setOptions

getOptions

setTestStructure

setModelHeader

buildClassifier

getModelHeader

getMappedClassIndex

constructMappedInstance

classifyInstance

distributionForInstance

toString

graphType

enumerateMeasures

getMeasure

graph

getRevision

main