InfoGainSplitCrit

java.lang.Object
- weka.classifiers.trees.j48.SplitCriterion
- - weka.classifiers.trees.j48.EntropyBasedSplitCrit
  - - weka.classifiers.trees.j48.InfoGainSplitCrit

All Implemented Interfaces:

java.io.Serializable, RevisionHandler
```
public final class InfoGainSplitCrit
extends EntropyBasedSplitCrit
```
Class for computing the information gain for a given distribution.

Version:

$Revision: 1.10 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor Description

InfoGainSplitCrit()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`java.lang.String`	`getRevision()`	Returns the revision string.
`double`	`splitCritValue(Distribution bags)`	This method is a straightforward implementation of the information gain criterion for the given distribution.
`double`	`splitCritValue(Distribution bags, double totalNoInst)`	This method computes the information gain in the same way C4.5 does.
`double`	`splitCritValue(Distribution bags, double totalNoInst, double oldEnt)`	This method computes the information gain in the same way C4.5 does.

Methods inherited from class weka.classifiers.trees.j48.EntropyBasedSplitCrit
logFunc, newEnt, oldEnt, splitEnt

Methods inherited from class weka.classifiers.trees.j48.SplitCriterion
splitCritValue, splitCritValue, splitCritValue

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

- Constructor Detail
  - InfoGainSplitCrit
```
public InfoGainSplitCrit()
```
- Method Detail
  - splitCritValue
```
public final double splitCritValue(Distribution bags)
```
    This method is a straightforward implementation of the information gain criterion for the given distribution.
    
    Overrides:
    
    splitCritValue in class SplitCriterion
    
    Returns:
    
    value of splitting criterion. 0 by default
  - splitCritValue
```
public final double splitCritValue(Distribution bags,
                                   double totalNoInst)
```
    This method computes the information gain in the same way C4.5 does.
    
    Parameters:
    
    bags - the distribution
    
    totalNoInst - weight of ALL instances (including the ones with missing values).
  - splitCritValue
```
public final double splitCritValue(Distribution bags,
                                   double totalNoInst,
                                   double oldEnt)
```
    This method computes the information gain in the same way C4.5 does.
    
    Parameters:
    
    bags - the distribution
    
    totalNoInst - weight of ALL instances
    
    oldEnt - entropy with respect to "no-split"-model.
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Returns:
    
    the revision