public class KStarNominalAttribute extends Object implements KStarConstants, RevisionHandler
Modifier and Type | Field and Description |
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protected int |
m_AttrIndex
The index of the nominal attribute in the test and train instances
|
protected double |
m_AverageProb
Average probability of test attribute transforming into train
attribute
|
protected int |
m_BlendFactor
default sphere of influence blend setting
|
protected int |
m_BlendMethod
B_SPHERE = use specified blend, B_ENTROPY = entropic blend setting
|
protected KStarCache |
m_Cache
A cache for storing attribute values and their corresponding
stop parameters
|
protected int |
m_ClassType
The class attribute type
|
protected int[] |
m_Distribution
Distribution of the attribute value in the train dataset
|
protected int |
m_MissingMode
missing value treatment
|
protected double |
m_MissingProb
Probability of test attribute transforming into train attribute
with missing value
|
protected int |
m_NumAttributes
The number of attributes
|
protected int |
m_NumClasses
The number of class values
|
protected int |
m_NumInstances
The number of instances in the dataset
|
protected int[][] |
m_RandClassCols
Set of colomns: each colomn representing a randomised version
of the train dataset class colomn
|
protected double |
m_SmallestProb
Smallest probability of test attribute transforming into
train attribute
|
protected double |
m_Stop
The stop parameter
|
protected Instance |
m_Test
The test instance
|
protected int |
m_TotalCount
Number of trai instances with no missing attribute values
|
protected Instance |
m_Train
The train instance
|
protected Instances |
m_TrainSet
The training instances used for classification.
|
B_ENTROPY, B_SPHERE, EPSILON, FLOOR, FLOOR1, INITIAL_STEP, LOG2, M_AVERAGE, M_DELETE, M_MAXDIFF, M_NORMAL, NUM_RAND_COLS, OFF, ON, ROOT_FINDER_ACCURACY, ROOT_FINDER_MAX_ITER
Constructor and Description |
---|
KStarNominalAttribute(Instance test,
Instance train,
int attrIndex,
Instances trainSet,
int[][] randClassCol,
KStarCache cache)
Constructor
|
Modifier and Type | Method and Description |
---|---|
String |
getRevision()
Returns the revision string.
|
void |
setOptions(int missingmode,
int blendmethod,
int blendfactor)
Sets the options.
|
double |
transProb()
Calculates the probability of the indexed nominal attribute of the test
instance transforming into the indexed nominal attribute of the training
instance.
|
protected Instances m_TrainSet
protected Instance m_Test
protected Instance m_Train
protected int m_AttrIndex
protected double m_Stop
protected double m_MissingProb
protected double m_AverageProb
protected double m_SmallestProb
protected int m_TotalCount
protected int[] m_Distribution
protected int[][] m_RandClassCols
protected KStarCache m_Cache
protected int m_NumInstances
protected int m_NumClasses
protected int m_NumAttributes
protected int m_ClassType
protected int m_MissingMode
protected int m_BlendMethod
protected int m_BlendFactor
public KStarNominalAttribute(Instance test, Instance train, int attrIndex, Instances trainSet, int[][] randClassCol, KStarCache cache)
public double transProb()
public void setOptions(int missingmode, int blendmethod, int blendfactor)
public String getRevision()
getRevision
in interface RevisionHandler
Copyright © 2015 University of Waikato, Hamilton, NZ. All rights reserved.