Package weka.classifiers

Class AbstractClassifier

java.lang.Object
weka.classifiers.AbstractClassifier
All Implemented Interfaces:
Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler
Direct Known Subclasses:
BayesNet, DecisionStump, DecisionTable, HoeffdingTree, IBk, J48, JRip, KStar, LinearRegression, LMT, Logistic, LogisticBase, M5Base, MultilayerPerceptron, MultipleClassifiersCombiner, NaiveBayes, NaiveBayesMultinomial, NaiveBayesMultinomialText, OneR, PART, PMMLClassifier, PreConstructedLinearModel, RandomizableClassifier, RandomTree, REPTree, RuleNode, SerializedClassifier, SimpleLinearRegression, SimpleLogistic, SingleClassifierEnhancer, SMO, SMOreg, VotedPerceptron, ZeroR
public abstract class AbstractClassifier extends Object implements Classifier, BatchPredictor, Cloneable, Serializable, OptionHandler, CapabilitiesHandler, RevisionHandler, CapabilitiesIgnorer, CommandlineRunnable
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: 15519 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)
See Also:

  • Field Details

    • NUM_DECIMAL_PLACES_DEFAULT

      public static int NUM_DECIMAL_PLACES_DEFAULT
      The number of decimal places used when printing numbers in the model.

    • BATCH_SIZE_DEFAULT

      public static String BATCH_SIZE_DEFAULT
      Default preferred batch size for batch predictions

  • Constructor Details

    • AbstractClassifier

      public AbstractClassifier()

  • Method Details

    • 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

    • runClassifier

      public static void runClassifier(Classifier classifier, String[] options)
      runs the classifier instance with the given options.
      Parameters:
      classifier - the classifier to run
      options - the commandline options

    • 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().
      Specified by:
      classifyInstance in interface Classifier
      Parameters:
      instance - 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 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().
      Specified by:
      distributionForInstance in interface Classifier
      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

    • listOptions

      public Enumeration<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Returns:
      an enumeration of all the available options.

    • 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

    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options. Valid options are:

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

      -do-not-check-capabilities
      If set, classifier capabilities are not checked before classifier is built (use with caution).

      -num-decimal-places
      The number of decimal places for the output of numbers in the model.

      -batch-size
      The desired batch size for batch prediction.

      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

    • getDebug

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

    • setDebug

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

    • 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

    • getDoNotCheckCapabilities

      public boolean getDoNotCheckCapabilities()
      Get whether capabilities checking is turned off.
      Specified by:
      getDoNotCheckCapabilities in interface CapabilitiesIgnorer
      Returns:
      true if capabilities checking is turned off.

    • setDoNotCheckCapabilities

      public void setDoNotCheckCapabilities(boolean doNotCheckCapabilities)
      Set whether not to check capabilities.
      Specified by:
      setDoNotCheckCapabilities in interface CapabilitiesIgnorer
      Parameters:
      doNotCheckCapabilities - true if capabilities are not to be checked.

    • doNotCheckCapabilitiesTipText

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

    • numDecimalPlacesTipText

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

    • getNumDecimalPlaces

      public int getNumDecimalPlaces()
      Get the number of decimal places.

    • setNumDecimalPlaces

      public void setNumDecimalPlaces(int num)
      Set the number of decimal places.

    • batchSizeTipText

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

    • setBatchSize

      public void setBatchSize(String size)
      Set the preferred batch size for batch prediction.
      Specified by:
      setBatchSize in interface BatchPredictor
      Parameters:
      size - the batch size to use

    • getBatchSize

      public String getBatchSize()
      Get the preferred batch size for batch prediction.
      Specified by:
      getBatchSize in interface BatchPredictor
      Returns:
      the preferred batch size

    • implementsMoreEfficientBatchPrediction

      public boolean implementsMoreEfficientBatchPrediction()
      Return true if this classifier can generate batch predictions in an efficient manner. Default implementation here returns false. Subclasses to override as appropriate.
      Specified by:
      implementsMoreEfficientBatchPrediction in interface BatchPredictor
      Returns:
      true if this classifier can generate batch predictions in an efficient manner.

    • distributionsForInstances

      public double[][] distributionsForInstances(Instances batch) throws Exception
      Batch prediction method. This default implementation simply calls distributionForInstance() for each instance in the batch. If subclasses can produce batch predictions in a more efficient manner than this they should override this method and also return true from implementsMoreEfficientBatchPrediction()
      Specified by:
      distributionsForInstances in interface BatchPredictor
      Parameters:
      batch - the instances to get predictions for
      Returns:
      an array of probability distributions, one for each instance in the batch
      Throws:
      Exception - if a problem occurs.

    • 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
      Specified by:
      getCapabilities in interface Classifier
      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

    • preExecution

      public void preExecution() throws Exception
      Perform any setup stuff that might need to happen before commandline execution. Subclasses should override if they need to do something here
      Specified by:
      preExecution in interface CommandlineRunnable
      Throws:
      Exception - if a problem occurs during setup

    • run

      public void run(Object toRun, String[] options) throws Exception
      Execute the supplied object.
      Specified by:
      run in interface CommandlineRunnable
      Parameters:
      toRun - the object to execute
      options - any options to pass to the object
      Throws:
      Exception - if the object is not of the expected type.

    • postExecution

      public void postExecution() throws Exception
      Perform any teardown stuff that might need to happen after execution. Subclasses should override if they need to do something here
      Specified by:
      postExecution in interface CommandlineRunnable
      Throws:
      Exception - if a problem occurs during teardown