edu.washington.cs.knowitall.extractor.conf
Class ReVerbIndependentConfFunction

java.lang.Object
  edu.washington.cs.knowitall.extractor.conf.ReVerbIndependentConfFunction

All Implemented Interfaces:

ConfidenceFunction

public class ReVerbIndependentConfFunction
extends Object
implements ConfidenceFunction

An extraction confidence function that is backed by a logistic regression classifier. This function will assign an extraction a real valued number between 0 and 1 according to the logistic regression model. It represents an extraction using the boolean features defined by the ReVerbFeatures class. See that documentation for details.

Author:

schmmd

Constructor Summary

ReVerbIndependentConfFunction()
Constructs a new instance of the confidence function.

ReVerbIndependentConfFunction(String model)

Method Summary

double

getConf(ChunkedBinaryExtraction extr)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ReVerbIndependentConfFunction

public ReVerbIndependentConfFunction()
                              throws ConfidenceFunctionException

Constructs a new instance of the confidence function.

Throws:

ConfidenceFunctionException - if unable to initialize

ReVerbIndependentConfFunction

public ReVerbIndependentConfFunction(String model)

Method Detail

getConf

public double getConf(ChunkedBinaryExtraction extr)
               throws ConfidenceFunctionException

Specified by:

getConf in interface ConfidenceFunction

Parameters:

extr -

Returns:

the probability that the given extraction belongs to the positive class

Throws:

ConfidenceFunctionException - if unable to compute the confidence score