java.lang.Object
- weka.estimators.Estimator
- - weka.estimators.KernelEstimator

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, CapabilitiesHandler, OptionHandler, RevisionHandler, IncrementalEstimator
```
public class KernelEstimator
extends Estimator
implements 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:

Serialized Form

Constructor Summary

Constructors
Constructor Description

KernelEstimator(double precision)
Constructor that takes a precision argument.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`addValue(double data, double weight)`	Add a new data value to the current estimator.
`Capabilities`	`getCapabilities()`	Returns default capabilities of the classifier.
`double[]`	`getMeans()`	Return the means of the kernels.
`int`	`getNumKernels()`	Return the number of kernels in this kernel estimator
`double`	`getPrecision()`	Return the precision of this kernel estimator.
`double`	`getProbability(double data)`	Get a probability estimate for a value.
`java.lang.String`	`getRevision()`	Returns the revision string.
`double`	`getStdDev()`	Return the standard deviation of this kernel estimator.
`double[]`	`getWeights()`	Return the weights of the kernels.
`static void`	`main(java.lang.String[] argv)`	Main method for testing this class.
`java.lang.String`	`toString()`	Display a representation of this estimator

Methods inherited from class weka.estimators.Estimator
addValues, addValues, addValues, addValues, buildEstimator, buildEstimator, clone, debugTipText, equals, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions, testCapabilities

Methods inherited from class java.lang.Object
getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - 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.
- Method Detail
  - addValue
```
public void addValue(double data,
                     double weight)
```
    Add a new data value to the current estimator.
    
    Specified by:
    
    addValue in interface IncrementalEstimator
    
    Overrides:
    
    addValue in class Estimator
    
    Parameters:
    
    data - the new data value
    
    weight - the weight assigned to the data value
  - getProbability
```
public double getProbability(double data)
```
    Get a probability estimate for a value.
    
    Specified by:
    
    getProbability in class Estimator
    
    Parameters:
    
    data - the value to estimate the probability of
    
    Returns:
    
    the estimated probability of the supplied value
  - toString
```
public java.lang.String toString()
```
    Display a representation of this estimator
    
    Overrides:
    
    toString in class java.lang.Object
  - getNumKernels
```
public int getNumKernels()
```
    Return the number of kernels in this kernel estimator
    
    Returns:
    
    the number of kernels
  - getMeans
```
public double[] getMeans()
```
    Return the means of the kernels.
    
    Returns:
    
    the means of the kernels
  - getWeights
```
public double[] getWeights()
```
    Return the weights of the kernels.
    
    Returns:
    
    the weights of the kernels
  - getPrecision
```
public double getPrecision()
```
    Return the precision of this kernel estimator.
    
    Returns:
    
    the precision
  - getStdDev
```
public double getStdDev()
```
    Return the standard deviation of this kernel estimator.
    
    Returns:
    
    the standard deviation
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Estimator
    
    Returns:
    
    the capabilities of this classifier
    
    See Also:
    
    Capabilities
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - should contain a sequence of numeric values

Class KernelEstimator

Constructor Summary

Method Summary

Methods inherited from class weka.estimators.Estimator

Methods inherited from class java.lang.Object

Constructor Detail

KernelEstimator

Method Detail

addValue

getProbability

toString

getNumKernels

getMeans

getWeights

getPrecision

getStdDev

getCapabilities

getRevision

main