edu.stanford.nlp.sentiment

Class Evaluate

java.lang.Object

edu.stanford.nlp.sentiment.AbstractEvaluate

edu.stanford.nlp.sentiment.Evaluate

public class Evaluate
extends AbstractEvaluate

Author:

John Bauer

Field Summary

Fields inherited from class edu.stanford.nlp.sentiment.AbstractEvaluate

NF

Constructor Summary

Constructors

Constructor and Description
Evaluate(SentimentModel model)

Method Summary

Modifier and Type	Method and Description
static void	main(String[] args) Expected arguments are -model model -treebank treebank For example java edu.stanford.nlp.sentiment.Evaluate edu/stanford/nlp/models/sentiment/sentiment.ser.gz /u/nlp/data/sentiment/trees/dev.txt Other arguments are available, for example -numClasses.
void	populatePredictedLabels(List<Tree> trees) Sets the predicted sentiment label for all trees given.

Methods inherited from class edu.stanford.nlp.sentiment.AbstractEvaluate

approxAccuracy, approxCombinedAccuracy, countLengthAccuracy, countRoot, countTree, eval, eval, exactNodeAccuracy, exactRootAccuracy, lengthAccuracies, printConfusionMatrix, printLengthAccuracies, printSummary, reset

Methods inherited from class java.lang.Object

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

Constructor Detail

Evaluate

public Evaluate(SentimentModel model)

Method Detail

populatePredictedLabels

public void populatePredictedLabels(List<Tree> trees)

Description copied from class: AbstractEvaluate

Sets the predicted sentiment label for all trees given. This method sets the RNNCoreAnnotations.PredictedClass annotation for all nodes in all trees.

Specified by:

populatePredictedLabels in class AbstractEvaluate

Parameters:

trees - List of Trees to be annotated

main

public static void main(String[] args)

Expected arguments are -model model -treebank treebank
For example
java edu.stanford.nlp.sentiment.Evaluate edu/stanford/nlp/models/sentiment/sentiment.ser.gz /u/nlp/data/sentiment/trees/dev.txt Other arguments are available, for example -numClasses. See RNNOptions.java, RNNTestOptions.java and RNNTrainOptions.java for more arguments. The configuration is usually derived from the RNN model file, which is not available here as the predictions are external. It is the caller's responsibility to provide a configuration matching the settings of the external predictor. Flags of interest include -equivalenceClasses .