Class ReVerbClassifierTrainer

java.lang.Object
  ReVerbClassifierTrainer

public class ReVerbClassifierTrainer
extends java.lang.Object

Used to train the ReVerb confidence function using the features described by ReVerbFeatures. Given a set of LabeledBinaryExtraction instances, this class featurizes them and trains a logistic regression classifier using Weka's Logistic class. This class can be called from the command-line to train a classifier and save the resulting model to a file.

Author:

afader

Constructor Summary

ReVerbClassifierTrainer(java.lang.Iterable<edu.washington.cs.knowitall.extractor.conf.LabeledBinaryExtraction> examples, weka.classifiers.Classifier classifier)
Constructs and trains a new Logistic classifier using the given examples.

Method Summary

weka.classifiers.Classifier	getClassifier()
edu.washington.cs.knowitall.extractor.conf.WekaDataSet<edu.washington.cs.knowitall.nlp.extraction.ChunkedBinaryExtraction>	getDataSet()

Methods inherited from class java.lang.Object

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

Constructor Detail

ReVerbClassifierTrainer

public ReVerbClassifierTrainer(java.lang.Iterable<edu.washington.cs.knowitall.extractor.conf.LabeledBinaryExtraction> examples,
                               weka.classifiers.Classifier classifier)
                        throws java.lang.Exception

Constructs and trains a new Logistic classifier using the given examples.

Parameters:

examples -

Throws:

java.lang.Exception

Method Detail

getDataSet

public edu.washington.cs.knowitall.extractor.conf.WekaDataSet<edu.washington.cs.knowitall.nlp.extraction.ChunkedBinaryExtraction> getDataSet()

Returns:

the data set used to train the classifier

getClassifier

public weka.classifiers.Classifier getClassifier()

Returns:

the trained classifier.