weka.classifiers.misc

## Class 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, CapabilitiesHandler, CapabilitiesIgnorer, 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: 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.
    `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, 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 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]