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java.lang.Objectweka.attributeSelection.ASEvaluation
weka.attributeSelection.AttributeEvaluator
weka.attributeSelection.InfoGainAttributeEval
Class for Evaluating attributes individually by measuring information gain with respect to the class. Valid options are:
-M
Treat missing values as a seperate value.
-B
Just binarize numeric attributes instead of properly discretizing them.
Field Summary | |
private boolean |
m_Binarize
Just binarize numeric attributes |
private double[] |
m_InfoGains
The info gain for each attribute |
private boolean |
m_missing_merge
Treat missing values as a seperate value |
Constructor Summary | |
InfoGainAttributeEval()
Constructor |
Method Summary | |
java.lang.String |
binarizeNumericAttributesTipText()
Returns the tip text for this property |
void |
buildEvaluator(Instances data)
Initializes an information gain attribute evaluator. |
double |
evaluateAttribute(int attribute)
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute. |
boolean |
getBinarizeNumericAttributes()
get whether numeric attributes are just being binarized. |
boolean |
getMissingMerge()
get whether missing values are being distributed or not |
java.lang.String[] |
getOptions()
Gets the current settings of WrapperSubsetEval. |
java.lang.String |
globalInfo()
Returns a string describing this attribute evaluator |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] args)
Main method for testing this class. |
java.lang.String |
missingMergeTipText()
Returns the tip text for this property |
protected void |
resetOptions()
Reset options to their default values |
void |
setBinarizeNumericAttributes(boolean b)
Binarize numeric attributes. |
void |
setMissingMerge(boolean b)
distribute the counts for missing values across observed values |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
java.lang.String |
toString()
Describe the attribute evaluator |
Methods inherited from class weka.attributeSelection.ASEvaluation |
forName, makeCopies, postProcess |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
private boolean m_missing_merge
private boolean m_Binarize
private double[] m_InfoGains
Constructor Detail |
public InfoGainAttributeEval()
Method Detail |
public java.lang.String globalInfo()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
Valid options are:
-M
Treat missing values as a seperate value.
-B
Just binarize numeric attributes instead of properly discretizing them.
setOptions
in interface OptionHandler
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public java.lang.String binarizeNumericAttributesTipText()
public void setBinarizeNumericAttributes(boolean b)
b
- true=binarize numeric attributespublic boolean getBinarizeNumericAttributes()
public java.lang.String missingMergeTipText()
public void setMissingMerge(boolean b)
b
- true=distribute missing values.public boolean getMissingMerge()
public void buildEvaluator(Instances data) throws java.lang.Exception
buildEvaluator
in class ASEvaluation
data
- set of instances serving as training data
java.lang.Exception
- if the evaluator has not been
generated successfullyprotected void resetOptions()
public double evaluateAttribute(int attribute) throws java.lang.Exception
evaluateAttribute
in class AttributeEvaluator
attribute
- the index of the attribute to be evaluated
java.lang.Exception
- if the attribute could not be evaluatedpublic java.lang.String toString()
public static void main(java.lang.String[] args)
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