weka.classifiers.trees.ht

## Class GaussianConditionalSufficientStats

- java.lang.Object
- - weka.classifiers.trees.ht.ConditionalSufficientStats
  - - weka.classifiers.trees.ht.GaussianConditionalSufficientStats

- All Implemented Interfaces:
    java.io.Serializable

      public class GaussianConditionalSufficientStats
      extends ConditionalSufficientStats
      implements java.io.Serializable

  Maintains sufficient stats for a Gaussian distribution for a numeric attribute
  Version:
    $Revision: 9705 $
  Author:
    Richard Kirkby (rkirkby@cs.waikato.ac.nz), Mark Hall (mhall{[at]}pentaho{[dot]}com)
  See Also:
    Serialized Form

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `GaussianConditionalSufficientStats()`

  - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `SplitCandidate` | `bestSplit(SplitMetric splitMetric, java.util.Map<java.lang.String,WeightMass> preSplitDist, java.lang.String attName)` Return the best split
    `int` | `getNumBins()`
    `double` | `probabilityOfAttValConditionedOnClass(double attVal, java.lang.String classVal)` Return the probability of an attribute value conditioned on a class value
    `void` | `setNumBins(int b)`
    `void` | `update(double attVal, java.lang.String classVal, double weight)` Update this stat with the supplied attribute value and class value

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Constructor Detail

    - #### GaussianConditionalSufficientStats

          public GaussianConditionalSufficientStats()

  - ### Method Detail

    - #### setNumBins

          public void setNumBins(int b)

    - #### getNumBins

          public int getNumBins()

    - #### update

          public void update(double attVal,
                             java.lang.String classVal,
                             double weight)

      Description copied from class: `ConditionalSufficientStats`
      Update this stat with the supplied attribute value and class value
      Specified by:
        `update` in class `ConditionalSufficientStats`
      Parameters:
        `attVal` - the value of the attribute
        `classVal` - the class value
        `weight` - the weight of this observation

    - #### probabilityOfAttValConditionedOnClass

          public double probabilityOfAttValConditionedOnClass(double attVal,
                                                              java.lang.String classVal)

      Description copied from class: `ConditionalSufficientStats`
      Return the probability of an attribute value conditioned on a class value
      Specified by:
        `probabilityOfAttValConditionedOnClass` in class `ConditionalSufficientStats`
      Parameters:
        `attVal` - the attribute value to compute the conditional probability for
        `classVal` - the class value
      Returns:
        the probability

    - #### bestSplit

          public SplitCandidate bestSplit(SplitMetric splitMetric,
                                          java.util.Map<java.lang.String,WeightMass> preSplitDist,
                                          java.lang.String attName)

      Description copied from class: `ConditionalSufficientStats`
      Return the best split
      Specified by:
        `bestSplit` in class `ConditionalSufficientStats`
      Parameters:
        `splitMetric` - the split metric to use
        `preSplitDist` - the distribution of class values prior to splitting
        `attName` - the name of the attribute being considered for splitting
      Returns:
        the best split for the attribute