All Classes

Class	Description
AADTWAggregatingFunction	Aggregation based on Arcs Dynamic Time Warping.
AberrantDialog	AberrantDialog is the dialog used to find aberrant values.
AbstractAggregatingFunction	Method to aggregate series, i.e. to estimate center/mean.
AbstractClassificationMetaLearner	Classification meta supervised learner is a meta-learner aimed to perform a classification task.
AbstractCommandablePanel	AbstractCommandableTab is an abstract class for command panels that implement common command panel methods.
AbstractCommandableTab	An AbstractCommandableTab is a tab that has a command panel.
AbstractCommandPanel	AbstractCommandPanel class describes the command panel (at the bottom of the screen).
AbstractCompetitiveNetwork	AbstractComptetitiveNetwork represents the base for Competitive Algorithms (implemented in NG, GNG, Kohonen, KMeans ...).
AbstractCompetitiveNetworkCommandPanel	AbstractCompetitiveNetworkCommandPanel is the super class of all unsupervised network command panels.
AbstractCorpus	AbstractCorpus class describes any corpus.
AbstractCorpusExporter	CorpusExporter provides an interface for corpus exportation depending on corpus type.
AbstractCriterion	This class defines common attribute and method for both evaluation and stopping criterion.
AbstractDataLoader	DataLoader is an abstract Class for Data Loader.
AbstractDecisionTree	DecisionTree class represents any decision tree.
AbstractDistanceFunction	DistanceFunction class represents any distance function of any competitive neural network.
AbstractEmbedded	This is the main class of variable's selection's methods of type embedded.
AbstractErrorFunction	ErrorFunction class represents any error function of any neural network.
AbstractEvaluationCriterion	EvaluationCriterion Abstract class represents a evaluation criterion for any features set.
AbstractFeatureSelection	This is the super class of all the variable's selection's methods; i.e. filter, wrapper and embedded method's approach.
AbstractFileCorpus	AbstractFileCorpus is the common class that describes corpus given from a file.
AbstractFilter	Abstract filter.
AbstractFSApproach	This is the main FeatureSelection's Class for the wrapper and embedded method's approach.
AbstractInformationFunction	AbstractInformationFunction evaluates quantity of information in a decision tree.
AbstractKernelFunction	KernelFunction Abstract class represents a kernel function for Kohonen algorithm.
AbstractLearningRateFunction	LearningRateFunction Abstract class represents a learning rate function for any neural network.
AbstractMetaSupervisedLearner	Meta supervised learner is a data-mining method that learn how to learn from learners.
AbstractMethodCommandPanel	A command panel for any datamining method.
AbstractMethodTab	AbstractMethodTab is the super class of any datamining method tab.
AbstractModelEvaluationCriterion	This class defines a criterion which evaluate a supervised model like perceptron or decision tree
AbstractModelStoppingCriterion	This class define criterion which compare an evaluation of the model and a value compute with model's parameter. This kind of criterion are used for classification or regression.
AbstractNetworkCommandPanel	AbstractNetworkCommandPanel is the super class of all network command panels.
AbstractNetworkCreationDialog	This dialog is the super class of all network creation dialogs.
AbstractNetworkView	AbstractNetworkView is a panel displaying any network with a graphical representation.
AbstractNeuralNetwork	A neural network.
AbstractOBD	Abstract class that regroups comportment shared by all Optimal Brain Damage-like pruning algorithms, for connection or neuron pruning of Perceptron models.
AbstractSaliencyEvaluationCriterion	AbstractSaliencyEvaluationCriterion abstract class concerns model evaluation criteria whose evaluation method are based on saliency computation.
AbstractSampler	A sampler creates n learners, sample patterns and distribute them to sub-learners.
AbstractSigmaFunction	Kernel function that need an initial and a final value for Sigma.
AbstractSimpleEvaluationCriterion	This class defines a criterion which evaluate variable set as entries or corpus for example.
AbstractSimpleStoppingCriterion	This class defines stopping criterion which compare two evaluations.
AbstractStatsTableModel	AbstractStatsTableModel is a model for stats table.
AbstractStoppingCriterion	StoppingCriterion Abstract class represents a criterion to stop the search of a better relevant features sub-set.
AbstractStoppingFunction	StoppingFunction Abstract class represents a stopping criterion for any stoppable data-mining method.
AbstractStrategy	AbstractStrategy describes an abstract class whose sub classes define different strategies.
AbstractSupervisedNetwork	SupervisedNetwork class represents a supervised network, like Perceptron.
AbstractTopologyFunction	TopologyFunction Abstract Class represents a topology function.
AbstractTransferFunction	TransferFunction class describes any transfert functions of any unit.
AbstractWrapper	This is the main class of variable's selection's methods of type wrapper.
AdaBoost	AdaBoost (ADAptative BOOSTing) is a probabilistic boosting method.
AdaBoostSamplerAndCombiner	AdaBoostSamplerAndCombiner implements AdaBoost algorithm for sampling and combinaison.
AdaptativeLearningRateFunction	AdaptativeLearningRateFunction class represents a learning rate function for any neural network which is adapted to the variation of the error of the neural network.
AddColumnDialog	AddColumnDialog is a common menu used to add column into Dataobjects.
AkaikeEvaluationCriterion	This class computes the Akaike Information Criteria (AIC).
Arcing	Arcing (Adaptatively Resample and Combine) is a probabilistic learning method.
ArcingSampler	ArcingSampler implements AdaBoost algorithm for sampling.
Attribute	Attribute is an object representing an attribute.
Attributes	Attributes is an interface that regroups all operations on pattern attributes.
AutoOBDDialog	TargetDialog is the "recode target" dialog.
AuxTableModel	AuxTableModel class describes table model for the second table (targets and labels).
BackwardFilter	This class generates a method backward for variable selection on corpus.
BackwardWrapper	This is the class which implements the Backward search's method as a wrapper method (which means that it works on the model, instead of on the data as it is the case for the BackwardFilter.
Bagging	Bagging is a boostrap implementation.
BaggingSampler	BaggingSampler sample patterns using boostrap.
BarChart	BarChart is a chart component
BarChartDialog	BarChartDialog is a dialog used to create chart for numerical data.
Bias	Bias.
BinaryFileDataLoader	BinaryFileDataLoader is a class implementation for BinaryFileDataLoader.
Bond	A Bond is a topological link between neighbor units.
Bootstrap	This class gives static access to boostrap sampling method.
BubbleKernelFunction	KernelFunctionBubble class represents a kernel function using Bubble.
C45	C45 class is an implementation of C4.5 algorithm.
CART	CART class is the implementation for CART decision tree algorithm.
CategorizationCorpus	CategorizationCorpus describes any corpus whose task is to categorize data.
CategorizationCorpusExporter	CategorizationCorpusExporter provides an interface for categorization corpus exportation.
CheckBoxValider	Action Listener for tokens checkboxes
ClassificationCorpus	ClassificationCorpus describes any corpus aimed to classify.
ClassificationCorpusExporter	CategorizationCorpusExporter provides an interface for categorization corpus exportation.
ClassificationErrorFunction	ClassificationErrorFunction is an error function made for classification networks.
ClassificationMethod	This interface describes common points of all classification methods.
CloseTabIcon	The class which generates the 'X' icon for the tabs.
ClusteringMethod	This interface describes common points of all clustering methods.
ColorCellRenderer	ColorCellRenderer class describes renderer for every table in the main window.
Combiner	Combiner provides an interface for all combining methods.
CombinerPanel
ComboEditor	Editor for symbolical data
CompetitiveNetworkVisitor	CompetitiveNetworkVisitor implements visitor design pattern for any competitive network.
CompetitivePopulation	CompetitivePopulation class represents a Population for competitive learning.
ConcreteStrategy	ConcreteStrategy defines a concrete strategy class.
ConfidenceComputer	ConfidendeComputer is a class that computes confidence interval and uncertainty for any classification method.
ConfuseRenderer	Renderer of the cells of the confuse table
ConfuseTableModel	ConfuseTableModel is a model for the confusion matrix table.
ConnectionGraph	ConnectionGraph is a graphical representation of a connection between two units.
ConnectionPruner	Embedded variable selection method that prune connections.
ConnectionSaliencyQuantityEvaluationCriterion	Evaluation criterion that selects a given number (called quantity) of worst connection to prune.
ConnectionSaliencyTresholdEvaluationCriterion	Evaluation criterion that selects all connection whose saliency in lower than given treshold.
ConstantLearningRateFunction	ConstantLearningRateFunction class represents a learning rate function for any neural network.
Coordinate	Any x y coordinate.
Copy	This class allows copies of files and directories.
CorpusCommandPanel	A CorpusCommandPanel is a command panel for any corpus.
CorpusCommentDialog	CorpusCommentDialog displays a dialog that allow to edit corpus comment.
CorpusTab	TabCorpus Class is part of the UI dedicated to corpus.
CorpusTableModel	DataTableModel is a model for the corpus data table.
CorrelationEvaluationCriterion	This class defines the covariance criterion.
CorrelationMatrixModel	CorrelationMatrixModel is a model for the correlation matrix table.
CriterionException	This class defines exception for evaluation or stopping criteria
CrossEntropyErrorFunction	CrossEntropyErrorFunction
CrossValidDialog	CrossValidDialog is a dialog used to choose cross validation options.
CubeTopologyFunction	TopologyFunctionCube class represents a topology function.
CycleStoppingCriterion	Stopping criterion that stops pruning after a given number of pruning cycles has been done.
Data	Data class represents a Data container.
DataCommandPanel	DataCommandPanel is the command panel for datas.
DataExporter	DataExporter.
DataMenu	DataMenu class describes common menu used by TabData objects.
DataMiningMethod	This interface defines common properties and comportement of all data-mining methods used in GINNet.
DataTab	DataTab is the part of the UI dedicated to Data
DataTableModel	DataTableModel is the model for the data table.
DBConnection	DBConnection is a class used to load a connection to a specific SGBD.
DBDataLoader	DBDataLoader is a class for DataBase Data Loader.
DBImportTableModel	This class is used as the model for the table that lets the user choose the data type for each column.
DBImportTableRenderer	The class is a modified renderer that shows a ComboBox in the first line.
DBWizard	DBWizard is the wizard to import data from databases.
DecreasingLearningRateFunction	DecreasingLearningRateFunction class represents a learning rate function for any neural network which decreases in time.
DimensionPanel	Panel where dimensions (1D, 2D or 3D ; x, y and z sizes and topology type) can be set.
DTWDistanceFunction	Implementation of Dynamic Time Warping algorithm to compute distance/error between desired and computed prototype.
DynamicLayerGraph	DynamicLayerGraph is a graphical representation of a GNG Layer.
DynNetConstants	This class regroups constants usefull for all DynNet and GINNet classes.
DynNetException	An exception thrown by DynNet.
DynnetMath	This class implements mathematical functions. You should use this methods in a static way.
DynnetMathException	this class defines an exception type for dynnet math utilities.
DynnetMatrix	DynnetMatrix class implements mathematics operations on matrix. All methods have static access.
DynNetPreferences	DynNetPreferences manages preferences for DynNet (and GINNet).
DynnetVector	DynnetVector implements mathematics operations on vector. All methods have static access.
EditTargetTableModel	EditTargetTableModel is the model for the edit target table.
EEGSignal	EEGSignal
EEGSignalLoader	EEGSignalLoader
Entries	Entries defines an interface for easy manipulable patterns.
Entropy	Entropy is the class used to evaluate quantity of information based on entropy in a decision tree.
EquiprobabilityDialog	This dilog allow to parametrize equiprobability, i.e. to choose percentage of tolerance and min or max mode.
ErrorEvaluationCriterion	ErrorEvaluationCriterion is a model based evaluation criterion that evaluate model by computing its error.
ErrorStoppingCriterion	Stopping criterion that stops pruning when a given error is reached.
ErrorStoppingFunction	ErrorStoppingFunction class represents a stopping criterion for any neural network.
EuclideanAggregatingFunction	Basic aggregation.
EuclideanDistanceFunction	Basic distance function.
ExportToCorpusDialog	ExportToCorpusDialog is the dialog that let the user choose a corpus type for data exportation.
FieldPanel	FieldPanel creates a panel for a specific field given as a Field object.
FileDataLoader	FileDataLoader class is an implementation for FileDataLoader.
FilterDialog	FilterDialog is a dialog for any filter.
FindDialog	FindDialog is a dialog to find and replace values into Data.
FisherStoppingCriterion	This class defines the Fisher statistics stopping criterion.
FolderPanel	FolderPanel, used in PreferencesDialog, is a panel that allow to: -see folder title -see and edit folder path -browse directory to get folder path
ForecastCorpus	ForecastCorpus represents any corpus whose task is to forecast.
ForecastCorpusExporter	ForecastCorpusExporter provides an interface to export forecast corpus.
ForwardFilter	This class generates a method forward for variable selection on corpus.
Gaussian1KernelFunction	KernelFunctionGaussian1 class represents a KernelFunctionGaussian1.
Gaussian2KernelFunction	KernelFunctionGaussian2 class represents a KernelFunctionGaussian2.
GeologicCodeEncoder	GeologicCodeEncoder is an implementation for GeologicCodeEncoder.
GibbsTransferFunction	GibbsTransferFunction describes Gibbs transfert function.
Gini	Gini class is used to evaluate quantity of information based on Gini in a decision tree.
GINNet	GINNet class describes main window for the GUI.
GINNetMenus	This class regroups static methods to build GINNet menus.
GINNetThread	ThreadRun class computes the calculation thread.
GNG	GNG class represents a Growing Neural Gas network.
GNGCommandPanel	GNGCommandPanel class describes the command panel to control a GNG network.
GNGDialog	GNGDialog is a dialog used to create a GNG.
GNGNode	GNG Node class is used in a competitivePopulation.
GNGView	GNGView is a panel displaying a Growing Neural Gas.
Graph	Graph class represents chart components.
GraphCommandPanel	A GraphCommandPanel is a command panel that display a Graph, containing method informations evolving in time.
HelpFrame	HelpFrame display help on a frame.
HexaLayerGraph	HexaLayerGraph is a graphical representation of a hexagonal layer.
HexaNeuronGraph	HexaNeuronGraph is a graphical representation of a hexagonal neuron.
HexaTopologyFunction	HexaTopologyFunction class represents a topology function on a hexagonal map (in 2 dimensions) where each node has 6 neighbors.
HoKashyap	HoKashyap implements Ho-Kashyap's algorithm, that tells if two classes are linearly discriminable or not.
HoKashyapDialog	HoKashyapDialog is a dialog for HoKashyap algorithm.
HTMLResultsFactory	HTMLResultsFactory formats result in proper HTMl code.
ID3	ID3 is the implementation for ID3 algorithm.
ImportTableModel	Table model for the preview table
ImportTableRenderer	A modified DefaultTableCellRenderer that change the color of the specified first line in blue
ImportWizard	ImportWizard is a wizard to import data in text files to a Data object.
InputNeuronGraph	InputNeuronGraph is a graphical representation of an input neuron.
InputSupervisedPopulation	InputSupervisedPopulation class represents an input population of a supervised network.
IOMethods	In this class are regrouped some usefull methods to manipulate files.
IVisitorCorpus	IVisitorCorpus visits corpus classes.
IVisitorGNG	IVisitorGNG implements Visitor design pattern for growing neural gas.
IVisitorKohonen	IVisitorKohonen implements visitor design pattern for elements of Kohonen self-organizing maps.
IVisitorNG	IVisitorNG implements visitor design pattern for elements of Neural gas networks.
IVisitorPerceptron	IVisitorPerceptron implements Visitor design pattern for Perceptron classes.
JarFileFilter	JarFileFilter is a FileFilter that filter Jar files.
JarFileMaker	JarFileMaker provides a method to easily create a Jar file.
JSpinnerDialog	JSpinnerDialog class is similar to JOptioPane.showInputDialog() but with a JSpinner instead of a JTextField.
JTabbedPaneClose	JTabbedPane with closeable tabs.
JTableEx	JTableEx Class is a Custom JTable with row header and scrollpane.
JTableRowEditor	A modified JTable that allows different cell editor to each row
KMDialog	KMDialog is a dialog used to create a K-means.
KMeans	KMeans class represents a KMeans algorithm.
KmeansCommandPanel	KMeansCommandPanel is a command panel to control a KMeans network.
KMeansEuclideanAggregatingFunction	Basic aggregation for KMeans.
KMeansIVisitor	KMeansIVisitor implements visitor design pattern for elements of KMeans.
KMeansView	KMeansView is a panel displaying a KMeans.
Kohonen	Kohonen class represents a kohonen network.
KohonenCommandPanel	KohonenCommandPanel class describes the command panel to control a kohonen network.
KohonenDialog	KohonenDialog is dialog used to create a kohonen map.
KohonenNode	Kohonen Node class is used in a competitivePopulation.
KohonenView	KohonenView is a panel displaying a Kohonen map.
LabelledPatterns	LabelledPatterns describes patterns that contain labels.
LayerGraph	LayerGraph is a graphical representation of a layer.
LayoutPanel	LayoutPanel is a generic panel that can be used to set the values of a layout, i.e. a number of inputs and its (cols * rows) layout.
LerayEvaluationCriterion	This class implements an evaluation criterion presented by Leray in Feature Selection with neural network.
LikelihoodErrorFunction	LikelihoodErrorFunction
LinearTransferFunction	TransferFunctionLinear describes a linear transfert function.
LineRenderer
LineTopologyFunction	TopologyFunctionLine class represents a topology function where nodes are in line (in 1 dimension).
ListLabelledPatternsImpl	ListLabelledPatternsImpl describes a list implementation of LabelledPatterns.
ListPatternsImpl	ListPatternsImpl implements Patterns interface with ArrayList.
ListTargetedLabelledPatternsImpl	ListTargetedLabelledPatternsImpl is an ArrayList implementation of patterns that contains targets and labels.
ListTargetedPatternsImpl	ListTargetedPatternsImpl proposes an ArrayList implementation of targeted patterns.
LongTask	LongTask class represents a class that may perform a long task that needs a LongTaskDisplayer to inform the user about task progression.
LongTaskDialog	JFrame implementation of LongTaskDisplayer.
LongTaskDisplayer	LongTaskDisplayer allow different implementation of progression display.
MajorityVoteCombiner	The majority decides.
MaximizeStoppingCriterion	This class defines a criterion which stop search methods. Stop searching when new model doesn't maximize evaluation
MetaLearnerCommandPanel	The command panel of meta-learners
MetaLearnerGUIVisitor	MetaLearnerGUIVisitor is a visitor that visits meta-learner to display them into GUI.
MetaLearnerResultPanel	MetaLearnerResultPanel display results of a meta-learner: - its errors (learn, test and validation) - its predictions
MetaLearnerSubComponent	A MetaLearnerSubComponent is a sub-panel of meta-learning interface.
MetaLearnerSubPanel	MetaLearnerSubPanel describes sub elements of the meta-learner GUI.
MetaLearnerTab	MetaLearner tab is the tab where meta-learners are displayed.
MinimizeStoppingCriterion	This class defines a criterion which stop search methods. Stop searching when new model doesn't minimize evaluation
ModelFromDynNetCommentDialog	ModelFromDynNetCommentDialog displays a dialog that allow to enter a comment describing model from DynNet to save.
ModelFromDynNetCreationException	Exception that occurs while the creation of a model from DynNet.
ModelFromDynNetExporter	This class performs exporting to Jar file for any data-mining model.
ModelFromDynNetFactory
MSEErrorFunction	MSEErrorFunction describes Mean Square Error error function.
MyFilter	Filter for images format (screenshot menu item)
MySqlConnection	MySqlConnection is the class for MySql DataBase Loading.
NetworkTab	NetworkTab class is part of the UI dedicated to networks.
NeuralGas	NeuralGas class represents a Neural Gas network.
NeuralGasCommandPanel	NeuralGasCommandPanel class describes the command panel to control a neural gas network.
NeuralGasView	NeuralGasView is a panel displaying a Neural Gas network.
NeuronGraph	NeuronGraph is a graphical representation of a neuron.
NeuronNodeGraph	NeuronNodeGraph is a graphical representation of a node.
NeuronPruner	Embedded neuron selection method that prune neuron units.
NeuronUnit	Unit class represents a unit.
NeuronUnitGraph	NeuronUnitGraph is a graphical representation of a unit.
NGDialog	NGDialog is a dialog used to create a neural gas.
NoClassPredictedException	Exception that occured when a decision tree is unable to predict the class of a pattern.
Node	Node class is used in a competitivePopulation.
NumericalAttribute	SymbolicAttribute describes an Attribute with a String value.
NumericalStatsTableModel	NumericalStatsTableModel is the table model describing numerical attribute statistics and only them.
NumericEntries	NumericEntries are Entries containing (only) numerical attributes and targets.
NumericEntriesException	NumericEntriesException is an exception that occur when a cast into NumericEntries is tried while those entries are not numeric.
NumerizePatternsDialog	This dialog allow to transform one or more symbolic attributes into numerical attributes.
OBDDialog	This dialog allow configuration and launching of all OBD-like pruning methods, like Optimal Brain Damage and Optimal Cell Damage.
OBDTableModel	Table model for the preview table
OCDSaliencyEvaluationCriterion	Saliency evaluation criterion for Optimal Cell Damage algorithm.
OptimalBrainDamage	This class implements Optimal Brain Damage algorithm for Perceptron pruning.
OptimalBrainSurgeon	This class implements Optimal Brain Surgeon algorithm for Perceptron pruning.
OptimalCellDamage	This class implements Optimal Cell Damage algorithm for neural network pruning.
PanelDataExport	JFileChooser extension panel for data exportation
Patterns	Patterns describes all operations needed by a file corpus to manage its patterns.
PatternSeparationDialog	Dialog used to separate patterns in different types.
PCA	Principal Componant Analysis
PCADialog	PCADialog is a dialog for PCA.
Perceptron	Perceptron class represents a Perceptron.
PerceptronCommandPanel	PerceptronCommandPanel class describes the command panel to control a perceptron network.
PerceptronConnection	A connection of a Perceptron network.
PerceptronDialog	PerceptronDialog is a dialog used to create a Perceptron.
PerceptronLayerGraph	PerceptronLayerGraph is a graphical representation of a perceptron layer.
PerceptronProjection	A PerceptronProjection is a projection of a Perceptron network, that manages links between two layers of the Perceptron.
PerceptronView	PerceptronView is a panel displaying a Perceptron.
PermutationStoppingFunction	PermutationStoppingFunction class represents a stopping criterion for any unsupervised network.
Position	Position
PreferencesDialog	PreferencesDialog is a dialog where to watch/edit preferences saved in preference file.
Projection	Projection class manages links between populations.
PrunableComponent
PruningException	A PruningException is an exception that occured while pruning.
RecodeCellDialog	RecodeCellDialog is a dialog used to recode data cells.
RectTopologyFunction	RectTopologyFunction describes a topology function where map is rectangular (in 2 dimensions) so each node has 4 neighbors.
RedundantDialog	RedundantDialog is a dialog used to find and delete redundant lines.
RegressionMethod	This interface describes common points of all regression methods.
ResultableMethod	A ResultableMethod characterizes any method willing to display an HTML result.
ResultsTab	ResultsTab is the result panel show in a tab to display any ResultableMethod results.
ResultsTab.HTMLFilter
RingTopologyFunction	RingTopologyFunction represents a topology function where nodes are in ring (in 1 dimension).
RMSEErrorFunction	RMSEErrorFunction describes Root Mean Square Error error function.
RowEditorModel	This class stores differents TableCellEditor.
SamplerPanel	SamplerPanel is the panel of the Sampler.
SEErrorFunction	SEErrorFunction describes error computation based on Square Error.
Selectable	Selectable is an interface for selectable objects.
SelectedConnection	A SelectedConnection is a supervised connection selected by a pruning method to be remove.
SelectedNeuron	A SelectedNeuronn is a neuron unit selected by a pruning method to be remove.
SelectedVariable	This class discribes a variable selected by a filter method.
SFFSFilter	Sequential Forward Floating Selection Filter.
SigmoidTransferFunction	SigmoidTransferFunction is a sigmoid transfert function.
SimpleEntries
SimpleFisherStoppingCriterion	This class define the Fisher statistics stopping criterion for filter approach.
SimpleNumericEntries	Numeric entries implantation.
SingleLearnerFactory	SingleLearner is used to instanciates any object imlementing SingleSupervisedLearner.
SingleSupervisedLearner	A SingleSupervisedLearner is a supervised learner that can be used as sub-learner by a meta-learner.
StandardizeDialog	This dialog allow to standardize one or more attributes of a corpus.
StatsTab	StatsTab is a simple statistics table.
StoppableMethod	StoppableMethod defines an interface for all DataMiningMethod that can be stopped (by a stopping function).
StrategyPanel	LearningRateFunctionPanel creates a dynamic panel with 2 parts : On the first line, you choose a strategy with a ComboBox.
SubCombinerPanel
SubEntries	A SubEntries is a subset of Entries.
SubLearnerPanel	A SubLearnerPanel is the interface for a sub-learner.
SubNumericEntries	SubNumericEntries are sub entries of NumericEntries
SupervisedConnection	Connection class represents a connection between units.
SupervisedMethod	This interface defines common properties of all supervised method.
SupervisedNetworkFromDynNetExample	This class is an example of class that should be generated by DynNet in order to save a supervised neural network as a simple Java class.
SupervisedNetworkManager	This class is the core of the Supervised Network's manager allowing to manage supervised networks and variable's selection methods.
SupervisedPopulation	SupervisedPopulation class represents a population.
SymbolicalStatsTableModel	SymbolicalStatsTableModel is the table model describing symbolical attribute statistics and only them.
SymbolicAttribute	SymbolicAttribute describes an Attribute with a String value.
TanHTransferFunction	TransferFunctionTanH describes an hyperbolic tangent transfert function.
TargetDialog	TargetDialog is the "recode target" dialog.
TargetedLabelledPatterns	TargetedLabelledPatterns describes operations on patterns containing labels and targets.
TargetedPatterns	TargetedPatterns are patterns containing targets.
TestPatternSeparationDialog	PatternSeparationDialog is dialog used to separate learn and test patterns.
TestValidationPatternSeparationDialog	PatternSeparationDialog is dialog used to separate learn, test and validation patterns.
TextFileDataLoader	TextFileDataLoader is an implementation for FileDataLoader.
TimeStoppingFunction	TimeStoppingFunction class represents a stopping criterion for any neural network.
TOM	TOM is Temporal Organization Map, an extension of Kohonen Self-Organizing Map that manages spatiotemporal treatments.
TOMCommandPanel	Command panel of any TOM network.
TOMDialog	TOMDialog is the dialog used to create a new TOM network.
Topology	Bond class manages Bonds between Nodes (ex : GNG Network).
TreeCommandPanel	TreeCommandPanel class describes the command panel to control a decision tree.
TreeEntries	TreeEntries allow easy tree entries construction.
TreeNode	TreeNode is a node of a tree (i.e. an intersection or a leaf).
TreeNodeGraph	TreeNodeGraph is the class of a graphical representation of a node in a tree.
TreeTab	TreeTab is a panel containing the graphical representation of decision trees.
TreeView	A TreeView is a graphical representation of a decision tree.
UnsupervisedMethod	This interface defines common comportement of all unsupervised methods.
Variance	Variance is used to evaluate quantity of information based on Variance in a decision tree.
VisitorGUI	VisitorGUI is a panel that visits and display network models.
WaitDialog	WaitDialog is a dialog used to ask the user to wait (for long processes).
WilksEvaluationCriterion	This class defines the Wilks' criterion.
WinnerKernelFunction	WinnerKernelFunction defines a kernel that only contains the winner node (the one whose distance is 0).
WrapperDialog	WrapperDialog is the GUI to launch wrapper variable selection methods.