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java.lang.Objectorg.knime.base.node.mine.bfn.BasisFunctionPredictorRow
org.knime.base.node.mine.bfn.fuzzy.FuzzyBasisFunctionPredictorRow
public class FuzzyBasisFunctionPredictorRow
Constructor Summary | |
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FuzzyBasisFunctionPredictorRow(ModelContentRO pp)
Creates a new predictor as fuzzy rule. |
protected |
FuzzyBasisFunctionPredictorRow(RowKey key,
DataCell classLabel,
MembershipFunction[] mem,
int norm)
Creates a new predictor as fuzzy rule. |
Method Summary | |
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double |
compose(DataRow row,
double act)
Composes the degree of membership by using the disjunction of the tco-norm operator. |
double |
computeActivation(DataRow row)
Returns the compute activation of this input vector. |
double |
computeDistance(DataRow row)
|
double |
computeSpread()
Returns the aggregated spread of the core. |
MutableDouble[] |
getMaxs()
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MembershipFunction |
getMemship(int i)
Returns the membership for one dimension. |
MembershipFunction[] |
getMemships()
|
MutableDouble[] |
getMins()
|
int |
getNorm()
|
int |
getNrMemships()
Return number of memberships which is equivalent to the number of numeric input dimensions. |
int |
getNrUsedFeatures()
|
double |
overlap(BasisFunctionPredictorRow bf,
boolean symmetric)
Computes the overlapping of two fuzzy basisfunction based on their core spreads. |
void |
save(ModelContentWO pp)
Saves this row into a model content. |
Methods inherited from class org.knime.base.node.mine.bfn.BasisFunctionPredictorRow |
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getClassLabel, getDontKnowClassDegree, getId, getNumAllCoveredPattern, getNumCorrectCoveredPattern, getNumWrongCoveredPattern, getVariance, overlapping, toString |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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protected FuzzyBasisFunctionPredictorRow(RowKey key, DataCell classLabel, MembershipFunction[] mem, int norm)
key
- The id for this rule.classLabel
- The class label of this rule.mem
- An array of membership functions each per dimension.norm
- A fuzzy norm to combine activations via all dimensions.public FuzzyBasisFunctionPredictorRow(ModelContentRO pp) throws InvalidSettingsException
pp
- Content to read rule from.
InvalidSettingsException
- If the content is invalid.Method Detail |
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public double overlap(BasisFunctionPredictorRow bf, boolean symmetric)
overlap
in class BasisFunctionPredictorRow
bf
- the other fuzzy basis functionsymmetric
- if the result is proportional to both basis functions,
and thus symmetric, or if it is proportional to the area of
the basis function on which the function is called
public int getNrMemships()
public MembershipFunction getMemship(int i)
i
- Dimension index.
public MembershipFunction[] getMemships()
public void save(ModelContentWO pp)
save
in class BasisFunctionPredictorRow
pp
- the model content to save this row topublic double compose(DataRow row, double act)
compose
in class BasisFunctionPredictorRow
row
- rowact
- activation
computeActivation(DataRow)
,
Norm.computeTCoNorm(double,double)
public double computeActivation(DataRow row)
computeActivation
in class BasisFunctionPredictorRow
row
- input pattern
public double computeDistance(DataRow row)
computeDistance
in class BasisFunctionPredictorRow
row
- to compute distance with
public double computeSpread()
computeSpread
in class BasisFunctionPredictorRow
public int getNrUsedFeatures()
getNrUsedFeatures
in class BasisFunctionPredictorRow
public final int getNorm()
public final MutableDouble[] getMins()
public final MutableDouble[] getMaxs()
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