org.knime.base.node.mine.bfn.fuzzy
Class FuzzyBasisFunctionFactory

java.lang.Object
  extended by org.knime.base.node.mine.bfn.BasisFunctionFactory
      extended by org.knime.base.node.mine.bfn.fuzzy.FuzzyBasisFunctionFactory

public class FuzzyBasisFunctionFactory
extends BasisFunctionFactory

Basic interface for all basis function algorithms. Provides the function getNewBasisFunction() to initialise a new prototype. This interface is needed in order to create new prototypes in the general BasisFunctionLearner. Hence a BasisFunctionLearner would be initialised with an object of type BasisFunctionFactory. It is used as factory to create basisfunctions. One implementation of the BasisFunctionFactory; here represents the FuzzyBasisFunctionFactory object.

Author:
Thomas Gabriel, University of Konstanz
See Also:
FuzzyBasisFunctionLearnerRow, commit(RowKey, DataCell, DataRow)

Field Summary
 
Fields inherited from class org.knime.base.node.mine.bfn.BasisFunctionFactory
CLASS_COLUMN
 
Constructor Summary
FuzzyBasisFunctionFactory(int norm, int shrink, DataTableSpec spec, String[] targetColumns, int distance)
          Creates a new factory fuzzy basisfunction along with a Norm and a Shrink function.
 
Method Summary
 BasisFunctionLearnerRow commit(RowKey key, DataCell classInfo, DataRow row)
          Creates and returns a new row initialised with a class label and a center vector.
 int getNorm()
          Returns the upper bound for conflicting instances.
 int getShrink()
          Returns the lower bound for non-conflicting instances.
 void save(ModelContent pp)
          Saves to model content.
 
Methods inherited from class org.knime.base.node.mine.bfn.BasisFunctionFactory
createModelSpec, findDataColumns, getDistance, getMaximums, getMinimums, getModelSpec
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

FuzzyBasisFunctionFactory

public FuzzyBasisFunctionFactory(int norm,
                                 int shrink,
                                 DataTableSpec spec,
                                 String[] targetColumns,
                                 int distance)
Creates a new factory fuzzy basisfunction along with a Norm and a Shrink function.

Parameters:
norm - the choice of fuzzy norm
shrink - the choice of shrink procedure
spec - the data to retrieve all columns and class info from
targetColumns - the class info column in the data
distance - the choice of distance function
Method Detail

commit

public BasisFunctionLearnerRow commit(RowKey key,
                                      DataCell classInfo,
                                      DataRow row)
Creates and returns a new row initialised with a class label and a center vector.

Specified by:
commit in class BasisFunctionFactory
Parameters:
key - the key for this row
row - the initial center vector
classInfo - the class info
Returns:
A new basisfunction

getNorm

public final int getNorm()
Returns the upper bound for conflicting instances.

Returns:
the upper bound for activation

getShrink

public final int getShrink()
Returns the lower bound for non-conflicting instances.

Returns:
the lower bound for activation

save

public void save(ModelContent pp)
Saves to model content.

Overrides:
save in class BasisFunctionFactory
Parameters:
pp - the model content this is saved to.


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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