Uses of Interface
weka.core.AdditionalMeasureProducer

Packages that use AdditionalMeasureProducer

Package	Description
weka.classifiers.bayes
weka.classifiers.bayes.net
weka.classifiers.functions
weka.classifiers.lazy
weka.classifiers.meta
weka.classifiers.misc
weka.classifiers.rules
weka.classifiers.trees
weka.classifiers.trees.m5
weka.core.neighboursearch
weka.experiment

Uses of AdditionalMeasureProducer in weka.classifiers.bayes

Classes in weka.classifiers.bayes that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	BayesNet	Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.

Uses of AdditionalMeasureProducer in weka.classifiers.bayes.net

Classes in weka.classifiers.bayes.net that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	BayesNetGenerator	Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.
class	BIFReader	Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format. For more details on XML BIF see: Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).
class	EditableBayesNet	Bayes Network learning using various search algorithms and quality measures. Base class for a Bayes Network classifier.

Uses of AdditionalMeasureProducer in weka.classifiers.functions

Classes in weka.classifiers.functions that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	SimpleLogistic	Classifier for building linear logistic regression models.
class	SMOreg	SMOreg implements the support vector machine for regression.

Uses of AdditionalMeasureProducer in weka.classifiers.lazy

Classes in weka.classifiers.lazy that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	IBk	K-nearest neighbours classifier.

Uses of AdditionalMeasureProducer in weka.classifiers.meta

Classes in weka.classifiers.meta that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	AdditiveRegression	Meta classifier that enhances the performance of a regression base classifier.
class	AttributeSelectedClassifier	Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
class	Bagging	Class for bagging a classifier to reduce variance.
class	IterativeClassifierOptimizer	Chooses the best number of iterations for an IterativeClassifier such as LogitBoost using cross-validation or a percentage split evaluation.

Uses of AdditionalMeasureProducer in weka.classifiers.misc

Classes in weka.classifiers.misc that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	InputMappedClassifier	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.

Uses of AdditionalMeasureProducer in weka.classifiers.rules

Classes in weka.classifiers.rules that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	DecisionTable	Class for building and using a simple decision table majority classifier. For more information see: Ron Kohavi: The Power of Decision Tables.
class	JRip	This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
class	M5Rules	Generates a decision list for regression problems using separate-and-conquer.
class	PART	Class for generating a PART decision list.

Uses of AdditionalMeasureProducer in weka.classifiers.trees

Classes in weka.classifiers.trees that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	J48	Class for generating a pruned or unpruned C4.5 decision tree.
class	LMT	Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
class	M5P	M5Base.
class	RandomForest	Class for constructing a forest of random trees. For more information see: Leo Breiman (2001).
class	REPTree	Fast decision tree learner.

Uses of AdditionalMeasureProducer in weka.classifiers.trees.m5

Classes in weka.classifiers.trees.m5 that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	M5Base	M5Base.

Uses of AdditionalMeasureProducer in weka.core.neighboursearch

Classes in weka.core.neighboursearch that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	BallTree	Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search. The connection to dataset is only a reference.
class	CoverTree	Class implementing the CoverTree datastructure. The class is very much a translation of the c source code made available by the authors. For more information and original source code see: Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor.
class	FilteredNeighbourSearch	Applies the given filter before calling the given neighbour search method.
class	KDTree	Class implementing the KDTree search algorithm for nearest neighbour search. The connection to dataset is only a reference.
class	LinearNNSearch	Class implementing the brute force search algorithm for nearest neighbour search.
class	NearestNeighbourSearch	Abstract class for nearest neighbour search.
class	PerformanceStats	The class that measures the performance of a nearest neighbour search (NNS) algorithm.
class	TreePerformanceStats	The class that measures the performance of a tree based nearest neighbour search algorithm.

Uses of AdditionalMeasureProducer in weka.experiment

Classes in weka.experiment that implement AdditionalMeasureProducer

Modifier and Type	Class	Description
class	AveragingResultProducer	Takes the results from a ResultProducer and submits the average to the result listener.
class	ClassifierSplitEvaluator	A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
class	CostSensitiveClassifierSplitEvaluator	SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
class	CrossValidationResultProducer	Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
class	CrossValidationSplitResultProducer	Carries out one split of a repeated k-fold cross-validation, using the set SplitEvaluator to generate some results.
class	DatabaseResultProducer	Examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
class	DensityBasedClustererSplitEvaluator	A SplitEvaluator that produces results for a density based clusterer.
class	ExplicitTestsetResultProducer	Loads the external test set and calls the appropriate SplitEvaluator to generate some results. The filename of the test set is constructed as follows: <dir> + / + <prefix> + <relation-name> + <suffix> The relation-name can be modified by using the regular expression to replace the matching sub-string with a specified replacement string.
class	LearningRateResultProducer	Tells a sub-ResultProducer to reproduce the current run for varying sized subsamples of the dataset.
class	RandomSplitResultProducer	Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.
class	RegressionSplitEvaluator	A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.