Class Classifier

java.lang.Object
weka.classifiers.Classifier
All Implemented Interfaces:
Serializable, Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler
Direct Known Subclasses:
ADTree, AODE, AODEsr, BayesianLogisticRegression, BayesNet, CitationKNN, ClassificationViaClustering, ComplementNaiveBayes, ConjunctiveRule, DecisionStump, DecisionTable, DMNBtext, FT, GaussianProcesses, HNB, HyperPipes, IB1, IBk, Id3, IsotonicRegression, J48, J48graft, JRip, KStar, LADTree, LBR, LeastMedSq, LibLINEAR, LinearRegression, LMT, Logistic, LogisticBase, M5Base, MDD, MIDD, MILR, MINND, MIOptimalBall, MISMO, MISVM, MultilayerPerceptron, MultipleClassifiersCombiner, NaiveBayes, NaiveBayesMultinomial, NaiveBayesSimple, NBTree, NNge, OneR, PaceRegression, PART, PLSClassifier, PMMLClassifier, PreConstructedLinearModel, Prism, RandomForest, RandomizableClassifier, RandomTree, RBFNetwork, REPTree, Ridor, RuleNode, SerializedClassifier, SimpleLinearRegression, SimpleLogistic, SingleClassifierEnhancer, SMO, SMOreg, SPegasos, UserClassifier, VFI, VotedPerceptron, WAODE, Winnow, ZeroR

public abstract class Classifier extends Object implements Cloneable, Serializable, OptionHandler, CapabilitiesHandler, RevisionHandler
Abstract classifier. All schemes for numeric or nominal prediction in Weka extend this class. Note that a classifier MUST either implement distributionForInstance() or classifyInstance().
Version:
$Revision: 10485 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
See Also:
  • Constructor Details

    • Classifier

      public Classifier()
  • Method Details

    • buildClassifier

      public abstract void buildClassifier(Instances data) throws Exception
      Generates a classifier. Must initialize all fields of the classifier that are not being set via options (ie. multiple calls of buildClassifier must always lead to the same result). Must not change the dataset in any way.
      Parameters:
      data - set of instances serving as training data
      Throws:
      Exception - if the classifier has not been generated successfully
    • classifyInstance

      public double classifyInstance(Instance instance) throws Exception
      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().
      Parameters:
      instance - the instance to be classified
      Returns:
      the predicted most likely class for the instance or Instance.missingValue() if no prediction is made
      Throws:
      Exception - if an error occurred during the prediction
    • distributionForInstance

      public double[] distributionForInstance(Instance instance) throws Exception
      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().
      Parameters:
      instance - 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
    • forName

      public static Classifier forName(String classifierName, String[] options) throws Exception
      Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method. If the classifier implements OptionHandler and the options parameter is non-null, the classifier will have it's options set.
      Parameters:
      classifierName - the fully qualified class name of the classifier
      options - an array of options suitable for passing to setOptions. May be null.
      Returns:
      the newly created classifier, ready for use.
      Throws:
      Exception - if the classifier name is invalid, or the options supplied are not acceptable to the classifier
    • makeCopy

      public static Classifier makeCopy(Classifier model) throws Exception
      Creates a deep copy of the given classifier using serialization.
      Parameters:
      model - the classifier to copy
      Returns:
      a deep copy of the classifier
      Throws:
      Exception - if an error occurs
    • makeCopies

      public static Classifier[] makeCopies(Classifier model, int num) throws Exception
      Creates a given number of deep copies of the given classifier using serialization.
      Parameters:
      model - the classifier to copy
      num - the number of classifier copies to create.
      Returns:
      an array of classifiers.
      Throws:
      Exception - if an error occurs
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      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:

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

      Specified by:
      setOptions in interface OptionHandler
      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
      Returns:
      an array of strings suitable for passing to setOptions
    • setDebug

      public void setDebug(boolean debug)
      Set debugging mode.
      Parameters:
      debug - true if debug output should be printed
    • getDebug

      public boolean getDebug()
      Get whether debugging is turned on.
      Returns:
      true if debugging output is on
    • debugTipText

      public String debugTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getCapabilities

      public Capabilities getCapabilities()
      Returns the Capabilities of this classifier. Maximally permissive capabilities are allowed by default. Derived classifiers should override this method and first disable all capabilities and then enable just those capabilities that make sense for the scheme.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Returns:
      the capabilities of this object
      See Also:
    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Returns:
      the revision