Uses of Interface
weka.gui.beans.BeanCommon

Packages that use BeanCommon

Package	Description
weka.gui.beans

Uses of BeanCommon in weka.gui.beans

Classes in weka.gui.beans that implement BeanCommon

Modifier and Type	Class	Description
class	AbstractDataSink	Abstract class for objects that store instances to some destination.
class	AbstractEvaluator	Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
class	AbstractTestSetProducer	Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
class	AbstractTrainAndTestSetProducer	Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
class	AbstractTrainingSetProducer	Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
class	Appender	A bean that appends multiple incoming data connections into a single data set.
class	Associator	Bean that wraps around weka.associations.
class	AttributeSummarizer	Bean that encapsulates displays bar graph summaries for attributes in a data set.
class	ClassAssigner	Bean that assigns a class attribute to a data set.
class	Classifier	Bean that wraps around weka.classifiers
class	ClassifierPerformanceEvaluator	A bean that evaluates the performance of batch trained classifiers
class	ClassValuePicker
class	Clusterer	Bean that wraps around weka.clusterers
class	ClustererPerformanceEvaluator	A bean that evaluates the performance of batch trained clusterers
class	CostBenefitAnalysis	Bean that aids in analyzing cost/benefit tradeoffs.
class	CrossValidationFoldMaker	Bean for splitting instances into training ant test sets according to a cross validation
class	DataVisualizer	Bean that encapsulates weka.gui.visualize.VisualizePanel
class	Filter	A wrapper bean for Weka filters
class	FlowByExpression	A bean that splits incoming instances (or instance streams) according to the evaluation of a logical expression.
class	ImageSaver	Component that can accept ImageEvents and save their encapsulated images to a file.
class	ImageViewer	A KF component that can accept imageEvent connections in order to display static images in a popup window
class	IncrementalClassifierEvaluator	Bean that evaluates incremental classifiers
class	InstanceStreamToBatchMaker	Bean that converts an instance stream into a (batch) data set.
class	Join
class	Loader	Loads data sets using weka.core.converter classes
class	MetaBean	A meta bean that encapsulates several other regular beans, useful for grouping large KnowledgeFlows.
class	ModelPerformanceChart	Bean that can be used for displaying threshold curves (e.g.
class	PredictionAppender	Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.
class	Saver	Saves data sets using weka.core.converter classes
class	ScatterPlotMatrix	Bean that encapsulates weka.gui.visualize.MatrixPanel for displaying a scatter plot matrix.
class	SerializedModelSaver	A bean that saves serialized models
class	Sorter	Sorts incoming instances in ascending or descending order according to the values of user specified attributes.
class	StripChart	Bean that can display a horizontally scrolling strip chart.
class	SubstringLabeler	A bean that finds matches in string attribute values (using either substring or regular expression matches) and labels the instance (sets the value of a new attribute) according to the supplied label for the matching rule.
class	SubstringReplacer	A bean that can replace substrings in the values of string attributes.
class	TestSetMaker	Bean that accepts data sets and produces test sets
class	TextSaver	Simple component to save the text carried in text events out to a file
class	TextViewer	Bean that collects and displays pieces of text
class	TrainingSetMaker	Bean that accepts a data sets and produces a training set
class	TrainTestSplitMaker	Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data