Uses of Class
org.knime.base.node.mine.bfn.BasisFunctionLearnerRow

Packages that use BasisFunctionLearnerRow
org.knime.base.node.mine.bfn Contains abstract and util classes to train and perform prediction to rule models, also called BasisFunction models. 
org.knime.base.node.mine.bfn.fuzzy Contains the learner and predictor to train fuzzy rules and apply them to unknown data. 
org.knime.base.node.mine.bfn.radial Contains the PNN learner and predictor. 
 

Uses of BasisFunctionLearnerRow in org.knime.base.node.mine.bfn
 

Methods in org.knime.base.node.mine.bfn that return BasisFunctionLearnerRow
abstract  BasisFunctionLearnerRow BasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Returns a new row initialised by a DataRow as its initial center vector and a class label.
 BasisFunctionLearnerRow BasisFunctionIterator.nextBasisFunction()
          Returns the next row in the iteration.
 

Methods in org.knime.base.node.mine.bfn that return types with arguments of type BasisFunctionLearnerRow
 Map<DataCell,List<BasisFunctionLearnerRow>> BasisFunctionLearnerTable.getBasisFunctions()
          Returns the map of basis functions list for each class.
 

Methods in org.knime.base.node.mine.bfn with parameters of type BasisFunctionLearnerRow
 void BasisFunctionLearnerTable.addBasisFunction(BasisFunctionLearnerRow bf)
          Adds the given basis function to the list using its nominal value for class assignment.
abstract  boolean BasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow o, DataRow r)
          Compares coverage of this and another row.
 double BasisFunctionLearnerRow.computeCoverage(BasisFunctionLearnerRow bf)
          Computes the intersection of instances covered by this and the other basisfunction - its fraction to the total number of instances is returned.
 void BasisFunctionLearnerTable.removeBasisFunction(BasisFunctionLearnerRow bf)
          Removes the given basisfunction from the model and updates all internal members.
 

Constructor parameters in org.knime.base.node.mine.bfn with type arguments of type BasisFunctionLearnerRow
BasisFunctionModelContent(DataTableSpec spec, Map<DataCell,List<BasisFunctionLearnerRow>> bfs)
          Creates a new basis function model object.
 

Uses of BasisFunctionLearnerRow in org.knime.base.node.mine.bfn.fuzzy
 

Subclasses of BasisFunctionLearnerRow in org.knime.base.node.mine.bfn.fuzzy
 class FuzzyBasisFunctionLearnerRow
          Extends the general BasisFunctionLearnerRow object to act as rectangular fuzzy prototype.
 

Methods in org.knime.base.node.mine.bfn.fuzzy that return BasisFunctionLearnerRow
 BasisFunctionLearnerRow FuzzyBasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Creates and returns a new row initialised with a class label and a center vector.
 

Methods in org.knime.base.node.mine.bfn.fuzzy with parameters of type BasisFunctionLearnerRow
 boolean FuzzyBasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow o, DataRow r)
          Compares this basisfunction with the another one by the fuzzy rule's number of covered pattern.
 

Uses of BasisFunctionLearnerRow in org.knime.base.node.mine.bfn.radial
 

Subclasses of BasisFunctionLearnerRow in org.knime.base.node.mine.bfn.radial
 class RadialBasisFunctionLearnerRow
          This class extends the general BasisFunctionLearnerRow in order to use radial basis function prototypes for training.
 

Methods in org.knime.base.node.mine.bfn.radial that return BasisFunctionLearnerRow
 BasisFunctionLearnerRow RadialBasisFunctionFactory.commit(RowKey key, DataCell classInfo, DataRow row)
          Creates and returns a new RadialBasisFunctionLearnerRow initialized with a center vector and a class label.
 

Methods in org.knime.base.node.mine.bfn.radial with parameters of type BasisFunctionLearnerRow
 boolean RadialBasisFunctionLearnerRow.compareCoverage(BasisFunctionLearnerRow best, DataRow row)
          Compares this basis function with the other one by its standard deviation if the number of covered pattern is equal otherwise use this identification.
 



Copyright, 2003 - 2010. All rights reserved.
University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
You may not modify, publish, transmit, transfer or sell, reproduce, create derivative works from, distribute, perform, display, or in any way exploit any of the content, in whole or in part, except as otherwise expressly permitted in writing by the copyright owner or as specified in the license file distributed with this product.