Package org.knime.base.node.mine.bfn

Contains abstract and util classes to train and perform prediction to rule models, also called BasisFunction models.

See:
          Description

Interface Summary
BasisFunctionLearnerTable.MissingValueReplacementFunction General missing values replacement interface.
BasisFunctionPortObject.Creator Creator used to instantiate basisfunction predictor rows.
DegreeOfAffinity  
 

Class Summary
BasisFunctionAntisymmetricRowOverlap  
BasisFunctionFactory Factory class for BasisFunctionLearnerRow which automatically creates new basis functions of a certain type.
BasisFunctionFilterRow Inner class to separate an data input row into a new row which are the first n-1 double cells and returns the class label.
BasisFunctionIterator Iterator over all BasisFunctionLearnerRows within the model.
BasisFunctionLearnerNodeDialogPane Abstract dialog pane used showing a column filter panel for class column selected and a panel for general learner options.
BasisFunctionLearnerNodeDialogPanel Panel is used inside the basisfunction dialogs for general settings, such as distance function, shrink after commit, distance measure, missing value handling, and maximum number of epochs.
BasisFunctionLearnerNodeModel Abstract basisfunction model holding the trained rule table.
BasisFunctionLearnerNodeView<T extends BasisFunctionLearnerNodeModel> View to display basisfunction rule models.
BasisFunctionLearnerRow General BasisFunctionLearnerRow prototype which provides functions to shrink, cover, and reset rules; and to be compared with others by its coverage.
BasisFunctionLearnerTable This class implements the DDA-algorithm published by Berthold&Huber which iteratively introduces new basisfunctions and/or shrinks already existing ones of conflicting classes during the training algorithm.
BasisFunctionModelContent  
BasisFunctionPortObject  
BasisFunctionPredictorCellFactory This predictor cell factory predicts the passed rows using the underlying basisfunction model.
BasisFunctionPredictorNodeDialog A dialog to apply data to basis functions.
BasisFunctionPredictorNodeModel The basis function predictor model performing a prediction on the data from the first input and the radial basisfunction model from the second.
BasisFunctionPredictorRow Class presents a predictor row for basisfunctions providing method to apply unknown data (compose).
BasisFunctionPredictorRowIterator Class wraps a row iterator in order to exents the given DataRow elements by on cell (resp.
BasisFunctionRowInclusion  
BasisFunctionSymmetricRowOverlap Class computes a overlapping value between two basis functions.
BestGuessMissingValueReplacementFunction "Best Guess" replacement which searches for the best value in the model or just takes the mean if not available.
Distance Computes the Euclidean distance between two vectors.
IncorpMissingValueReplacementFunction Makes use the missing value by using it inside the model.
MaximumMissingValueReplacementFunction Maximum replacement.
MeanMissingValueReplacementFunction Mean replacement.
MinimumMissingValueReplacementFunction Minimum replacement.
OneMissingValueReplacementFunction One replacement.
ZeroMissingValueReplacementFunction Zero replacement.
 

Package org.knime.base.node.mine.bfn Description

Contains abstract and util classes to train and perform prediction to rule models, also called BasisFunction models.



Copyright, 2003 - 2010. All rights reserved.
University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
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