Class to define an input characteristic to the software. Attributes ---------- name : str Name of the input. values : li

Class representing a FIFO queue. @author Len Trigg (trigg@cs.waikato.ac.nz) @version $Revision: 1.7 $

Data structure for storing tests. Attributes ---------- function : str Name of the function to call i_fields : list of `

Class to define an input characteristic to the software. Attributes ---------- name : str Name of the input. values : li

Data structure for storing tests. Attributes ---------- function : str Name of the function to call i_fields : list of `

Compute discrimination for a piece of software. Attributes ---------- Methods -------

Compute discrimination for a piece of software. Attributes ---------- Methods -------

The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in

The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in

Class for generating an alternating decision tree. The basic algorithm is based on:<p> Freund, Y., Mason, L.: The alternating decision tree learning

Class for generating an alternating decision tree. The basic algorithm is based on:<p> Freund, Y., Mason, L.: The alternating decision tree learning

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence

Abstract attribute selection evaluation class @author Mark Hall (mhall@cs.waikato.ac.nz) @version $Revision: 1.9 $

Abstract attribute selection evaluation class @author Mark Hall (mhall@cs.waikato.ac.nz) @version $Revision: 1.9 $

Abstract attribute selection search class. @author Mark Hall (mhall@cs.waikato.ac.nz) @version $Revision: 1.8 $

Abstract attribute selection search class. @author Mark Hall (mhall@cs.waikato.ac.nz) @version $Revision: 1.8 $

Abstract class for objects that store instances to some destination. @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision

Abstract class for objects that store instances to some destination. @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision

Bean info class for the AbstractDataSink @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

Bean info class for the AbstractDataSink @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

Abstract class for objects that can provide instances from some source @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revisi

Abstract class for objects that can provide instances from some source @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revisi

Bean info class for AbstractDataSource. All beans that extend AbstractDataSource might want to extend this class @author <a href="mailto:mhall@cs.wai

Bean info class for AbstractDataSource. All beans that extend AbstractDataSource might want to extend this class @author <a href="mailto:mhall@cs.wai

Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc. @author <a href="mailto:mhall@cs.waikato.ac.nz">M

Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc. @author <a href="mailto:mhall@cs.waikato.ac.nz">M

Abstract class for Savers that save to a file Valid options are: -i input arff file <br> The input filw in arff format. <p> -o the output file <br>

Abstract class for Savers that save to a file Valid options are: -i input arff file <br> The input filw in arff format. <p> -o the output file <br>

Abstract class gives default implementation of setSource methods. All other methods must be overridden. @author Richard Kirkby (rkirkby@cs.waikato.ac

Abstract class gives default implementation of setSource methods. All other methods must be overridden. @author Richard Kirkby (rkirkby@cs.waikato.ac

Abstract class for Saver @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @author Stefan Mutter (mutter@cs.waikato.ac.nz) @version $Revision: 1.2 $

Abstract class for Saver @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @author Stefan Mutter (mutter@cs.waikato.ac.nz) @version $Revision: 1.2 $

Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation. @author <

Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation. @author <

BeanInfo class for AbstractTestSetProducer @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

BeanInfo class for AbstractTestSetProducer @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with at

An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with at

Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representatio

Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representatio

Bean info class for AbstractTrainAndTestSetProducers @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

Bean info class for AbstractTrainAndTestSetProducers @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation @autho

Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation @autho

BeanInfo class for AbstractTrainingSetProducer @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

BeanInfo class for AbstractTrainingSetProducer @author <a href="mailto:mhall@cs.waikato.ac.nz">Mark Hall</a> @version $Revision: 1.1 $

Class for boosting a classifier using Freund &amp; Schapire's Adaboost M1 method. For more information, see<p> Yoav Freund and Robert E. Schapire (19

Class for boosting a classifier using Freund &amp; Schapire's Adaboost M1 method. For more information, see<p> Yoav Freund and Robert E. Schapire (19

An instance filter that adds a new attribute to the dataset. The new attribute contains all missing values.<p> Valid filter-specific options are:<p>

An instance filter that adds a new attribute to the dataset. The new attribute contains all missing values.<p> Valid filter-specific options are:<p>

A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.<p> Valid filter-

A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.<p> Valid filter-

Applys a mathematical expression involving attributes and numeric constants to a dataset. A new attribute is appended after the last attribute that co

Applys a mathematical expression involving attributes and numeric constants to a dataset. A new attribute is appended after the last attribute that co

Introduces noise data a random subsample of the dataset by changing a given attribute (attribute must be nominal) Valid options are:<p> -C col <br>

Introduces noise data a random subsample of the dataset by changing a given attribute (attribute must be nominal) Valid options are:<p> -C col <br>

Interface to something that can produce measures other than those calculated by evaluation modules. @author Mark Hall (mhall@cs.waikato.ac.nz) @versi

Interface to something that can produce measures other than those calculated by evaluation modules. @author Mark Hall (mhall@cs.waikato.ac.nz) @versi

Meta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left by the classifier on

Meta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left by the classifier on

This panel controls setting a list of algorithms for an experiment to iterate over. @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @version $Revis

This panel controls setting a list of algorithms for an experiment to iterate over. @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) @version $Revis

A simple instance filter that passes all instances directly through. Basically just for testing purposes. @author Len Trigg (trigg@cs.waikato.ac.nz)

A simple instance filter that passes all instances directly through. Basically just for testing purposes. @author Len Trigg (trigg@cs.waikato.ac.nz)