Package weka.estimators
Class KernelEstimator
java.lang.Object
weka.estimators.Estimator
weka.estimators.KernelEstimator
- All Implemented Interfaces:
Serializable
,Cloneable
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,IncrementalEstimator
Simple kernel density estimator. Uses one gaussian kernel per observed
data value.
- Version:
- $Revision: 5540 $
- Author:
- Len Trigg (trigg@cs.waikato.ac.nz)
- See Also:
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Constructor Summary
ConstructorsConstructorDescriptionKernelEstimator
(double precision) Constructor that takes a precision argument. -
Method Summary
Modifier and TypeMethodDescriptionvoid
addValue
(double data, double weight) Add a new data value to the current estimator.Returns default capabilities of the classifier.double[]
getMeans()
Return the means of the kernels.int
Return the number of kernels in this kernel estimatordouble
Return the precision of this kernel estimator.double
getProbability
(double data) Get a probability estimate for a value.Returns the revision string.double
Return the standard deviation of this kernel estimator.double[]
Return the weights of the kernels.static void
Main method for testing this class.toString()
Display a representation of this estimatorMethods inherited from class weka.estimators.Estimator
addValues, addValues, addValues, addValues, buildEstimator, buildEstimator, clone, debugTipText, equals, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions, testCapabilities
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Constructor Details
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KernelEstimator
public KernelEstimator(double precision) Constructor that takes a precision argument.- Parameters:
precision
- the precision to which numeric values are given. For example, if the precision is stated to be 0.1, the values in the interval (0.25,0.35] are all treated as 0.3.
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Method Details
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addValue
public void addValue(double data, double weight) Add a new data value to the current estimator.- Specified by:
addValue
in interfaceIncrementalEstimator
- Overrides:
addValue
in classEstimator
- Parameters:
data
- the new data valueweight
- the weight assigned to the data value
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getProbability
public double getProbability(double data) Get a probability estimate for a value.- Specified by:
getProbability
in classEstimator
- Parameters:
data
- the value to estimate the probability of- Returns:
- the estimated probability of the supplied value
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toString
Display a representation of this estimator -
getNumKernels
public int getNumKernels()Return the number of kernels in this kernel estimator- Returns:
- the number of kernels
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getMeans
public double[] getMeans()Return the means of the kernels.- Returns:
- the means of the kernels
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getWeights
public double[] getWeights()Return the weights of the kernels.- Returns:
- the weights of the kernels
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getPrecision
public double getPrecision()Return the precision of this kernel estimator.- Returns:
- the precision
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getStdDev
public double getStdDev()Return the standard deviation of this kernel estimator.- Returns:
- the standard deviation
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getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classEstimator
- Returns:
- the capabilities of this classifier
- See Also:
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
argv
- should contain a sequence of numeric values
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