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java.lang.Objectweka.classifiers.AbstractClassifier
weka.classifiers.RandomizableClassifier
weka.classifiers.functions.RBFModel
public abstract class RBFModel
Abstract super class that can be extended by sub classes that learn RBF models.
Field Summary | |
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static Tag[] |
TAGS_SCALE
|
static int |
USE_GLOBAL_SCALE
Constants for scale optimization options |
static int |
USE_SCALE_PER_UNIT
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static int |
USE_SCALE_PER_UNIT_AND_ATTRIBUTE
|
Constructor Summary | |
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RBFModel()
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Method Summary | |
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void |
buildClassifier(Instances data)
Builds the RBF network regressor based on the given dataset. |
double[] |
distributionForInstance(Instance inst)
Calculates the output of the network after the instance has been piped through the fliters to replace missing values, etc. |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
int |
getNumFunctions()
Gets the number of functions. |
int |
getNumThreads()
Gets the number of threads. |
java.lang.String[] |
getOptions()
Gets the current settings of the Classifier. |
int |
getPoolSize()
Gets the number of threads. |
double |
getRidge()
Gets the value of the ridge parameter. |
SelectedTag |
getScaleOptimizationOption()
Gets the scale optimisation method to use. |
double |
getTolerance()
Gets the tolerance parameter for the delta values. |
boolean |
getUseAttributeWeights()
Gets whether to use attribute weights |
boolean |
getUseCGD()
Gets whether to use CGD. |
boolean |
getUseNormalizedBasisFunctions()
Gets whether to use normalized basis functions. |
java.lang.String |
globalInfo()
This will return a string describing the classifier. |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
java.lang.String |
numFunctionsTipText()
|
java.lang.String |
numThreadsTipText()
|
java.lang.String |
poolSizeTipText()
|
java.lang.String |
ridgeTipText()
|
java.lang.String |
scaleOptimizationOptionTipText()
|
void |
setNumFunctions(int newNumFunctions)
Sets the number of functions. |
void |
setNumThreads(int nT)
Sets the number of threads |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setPoolSize(int nT)
Sets the number of threads |
void |
setRidge(double newRidge)
Sets the value of the ridge parameter. |
void |
setScaleOptimizationOption(SelectedTag newMethod)
Sets the scale optimization option to use. |
void |
setTolerance(double newTolerance)
Sets the tolerance parameter for the delta values. |
void |
setUseAttributeWeights(boolean newUseAttributeWeights)
Sets whether to use attribute weights. |
void |
setUseCGD(boolean newUseCGD)
Sets whether to use CGD. |
void |
setUseNormalizedBasisFunctions(boolean newUseNormalizedBasisFunctions)
Sets whether to use normalized basis functions. |
java.lang.String |
toleranceTipText()
|
java.lang.String |
useAttributeWeightsTipText()
|
java.lang.String |
useCGDTipText()
|
java.lang.String |
useNormalizedBasisFunctionsTipText()
|
Methods inherited from class weka.classifiers.RandomizableClassifier |
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getSeed, seedTipText, setSeed |
Methods inherited from class weka.classifiers.AbstractClassifier |
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classifyInstance, debugTipText, forName, getDebug, getRevision, makeCopies, makeCopy, runClassifier, setDebug |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final int USE_GLOBAL_SCALE
public static final int USE_SCALE_PER_UNIT
public static final int USE_SCALE_PER_UNIT_AND_ATTRIBUTE
public static final Tag[] TAGS_SCALE
Constructor Detail |
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public RBFModel()
Method Detail |
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public Capabilities getCapabilities()
getCapabilities
in interface Classifier
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class AbstractClassifier
public void buildClassifier(Instances data) throws java.lang.Exception
java.lang.Exception
public double[] distributionForInstance(Instance inst) throws java.lang.Exception
distributionForInstance
in interface Classifier
distributionForInstance
in class AbstractClassifier
java.lang.Exception
public java.lang.String globalInfo()
public java.lang.String toleranceTipText()
public double getTolerance()
public void setTolerance(double newTolerance)
public java.lang.String numFunctionsTipText()
public int getNumFunctions()
public void setNumFunctions(int newNumFunctions)
public java.lang.String ridgeTipText()
public double getRidge()
public void setRidge(double newRidge)
public java.lang.String useCGDTipText()
public boolean getUseCGD()
public void setUseCGD(boolean newUseCGD)
public java.lang.String useAttributeWeightsTipText()
public boolean getUseAttributeWeights()
public void setUseAttributeWeights(boolean newUseAttributeWeights)
public java.lang.String useNormalizedBasisFunctionsTipText()
public boolean getUseNormalizedBasisFunctions()
public void setUseNormalizedBasisFunctions(boolean newUseNormalizedBasisFunctions)
public java.lang.String scaleOptimizationOptionTipText()
public SelectedTag getScaleOptimizationOption()
public void setScaleOptimizationOption(SelectedTag newMethod)
public java.lang.String numThreadsTipText()
public int getNumThreads()
public void setNumThreads(int nT)
public java.lang.String poolSizeTipText()
public int getPoolSize()
public void setPoolSize(int nT)
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class RandomizableClassifier
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-N Number of Gaussian basis functions (default is 2).
-R Ridge factor for quadratic penalty on output weights (default is 0.01).
-C The scale optimization option: global scale (1), one scale per unit (2), scale per unit and attribute (3) (default is 2).
-G Use conjugate gradient descent (recommended for many attributes).
-O Use normalized basis functions.
-A Use attribute weights.
-S <num> Random number seed. (default 1)
-D If set, classifier is run in debug mode and may output additional info to the consoleOptions after -- are passed to the designated classifier.
setOptions
in interface OptionHandler
setOptions
in class RandomizableClassifier
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class RandomizableClassifier
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