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## weka.estimators
Class KDConditionalEstimator

    java.lang.Object
      weka.estimators.KDConditionalEstimator

All Implemented Interfaces:
  RevisionHandler, ConditionalEstimator

    public class KDConditionalEstimator

extends java.lang.Object
implements ConditionalEstimator

Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).

Version:
  $Revision: 1.8 $
Author:
  Len Trigg (trigg@cs.waikato.ac.nz)

Constructor Summary
`KDConditionalEstimator(int numCondSymbols, double precision)` Constructor

Method Summary
`void` | `addValue(double data, double given, double weight)` Add a new data value to the current estimator.
`Estimator` | `getEstimator(double given)` Get a probability estimator for a value
`double` | `getProbability(double data, double given)` Get a probability estimate for a value
`java.lang.String` | `getRevision()` Returns the revision string.
`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 java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### KDConditionalEstimator

    public KDConditionalEstimator(int numCondSymbols,
                                  double precision)

  Constructor

  Parameters:
    `numCondSymbols` - the number of conditioning symbols
    `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 given,
                         double weight)

  Add a new data value to the current estimator.

  Specified by:
    `addValue` in interface `ConditionalEstimator`
  Parameters:
    `data` - the new data value
    `given` - the new value that data is conditional upon
    `weight` - the weight assigned to the data value

### getEstimator

    public Estimator getEstimator(double given)

  Get a probability estimator for a value

  Specified by:
    `getEstimator` in interface `ConditionalEstimator`
  Parameters:
    `given` - the new value that data is conditional upon
  Returns:
    the estimator for the supplied value given the condition

### getProbability

    public double getProbability(double data,
                                 double given)

  Get a probability estimate for a value

  Specified by:
    `getProbability` in interface `ConditionalEstimator`
  Parameters:
    `data` - the value to estimate the probability of
    `given` - the new value that data is conditional upon
  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`

### 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 pairs of integers which will be treated as numeric, symbolic.

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