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java.lang.Object edu.cmu.minorthird.classify.transform.InfoGainTransformLearner
public class InfoGainTransformLearner
A simple feature filter based on Ingormation Gain. The frequency model is resposible for deciding 'what to count'. If set to "document" this filter counts the number of documents which contain a Feature; if set to "word" this filter counts the number of times a Feature appears in the whole dataset.
Constructor Summary | |
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InfoGainTransformLearner()
Constructors |
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InfoGainTransformLearner(java.lang.String model)
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Method Summary | |
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InstanceTransform |
batchTrain(Dataset dataset)
Examine data, build an instance transformer |
double |
Entropy(double P1,
double P2)
compute the entropy of a binary attribute |
double |
getLength(Example e)
Get the total number of words in an Example |
static void |
main(java.lang.String[] args)
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void |
setSchema(ExampleSchema schema)
Accept an ExampleSchema - constraints on what the Examples will be. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public InfoGainTransformLearner()
public InfoGainTransformLearner(java.lang.String model)
Method Detail |
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public void setSchema(ExampleSchema schema)
setSchema
in interface InstanceTransformLearner
public InstanceTransform batchTrain(Dataset dataset)
batchTrain
in interface InstanceTransformLearner
public double Entropy(double P1, double P2)
public double getLength(Example e)
public static void main(java.lang.String[] args)
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