SplitCriterion (DiscriminationAwareProcessAnalysis)

java.lang.Object
- org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree.SplitCriterion

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

EntropyBasedSplitCrit
```
public abstract class SplitCriterion
extends java.lang.Object
implements java.io.Serializable
```
Abstract class for computing splitting criteria with respect to distributions of class values.

Version:

$Revision: 1.5 $

Author:

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

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor Description

SplitCriterion()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`splitCritValue(Distribution bags)`	Computes result of splitting criterion for given distribution.
`double`	`splitCritValue(Distribution train, Distribution test)`	Computes result of splitting criterion for given training and test distributions.
`double`	`splitCritValue(Distribution train, Distribution test, int noClassesDefault)`	Computes result of splitting criterion for given training and test distributions and given number of classes.
`double`	`splitCritValue(Distribution train, Distribution test, Distribution defC)`	Computes result of splitting criterion for given training and test distributions and given default distribution.

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

- Constructor Detail
  - SplitCriterion
```
public SplitCriterion()
```
- Method Detail
  - splitCritValue
```
public double splitCritValue(Distribution bags)
```
    Computes result of splitting criterion for given distribution.
    
    Returns:
    
    value of splitting criterion. 0 by default
  - splitCritValue
```
public double splitCritValue(Distribution train,
                             Distribution test)
```
    Computes result of splitting criterion for given training and test distributions.
    
    Returns:
    
    value of splitting criterion. 0 by default
  - splitCritValue
```
public double splitCritValue(Distribution train,
                             Distribution test,
                             int noClassesDefault)
```
    Computes result of splitting criterion for given training and test distributions and given number of classes.
    
    Returns:
    
    value of splitting criterion. 0 by default
  - splitCritValue
```
public double splitCritValue(Distribution train,
                             Distribution test,
                             Distribution defC)
```
    Computes result of splitting criterion for given training and test distributions and given default distribution.
    
    Returns:
    
    value of splitting criterion. 0 by default