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Class weka.classifiers.evaluation.EvaluationUtils

java.lang.Object
    |
    +----weka.classifiers.evaluation.EvaluationUtils

public class EvaluationUtils
extends java.lang.Object
Contains utility functions for generating lists of predictions in various manners.

Version:
$Revision: 1.6 $
Author:
Len Trigg (len@intelligenesis.net)

Constructor Index

 o EvaluationUtils()
 

Method Index

 o getCVPredictions(DistributionClassifier, Instances, int)
Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
 o getPrediction(DistributionClassifier, Instance)
Generate a single prediction for a test instance given the pre-trained classifier.
 o getSeed()
Gets the seed for randomization during cross-validation
 o getTestPredictions(DistributionClassifier, Instances)
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
 o getTrainTestPredictions(DistributionClassifier, Instances, Instances)
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
 o setSeed(int)
Sets the seed for randomization during cross-validation

Constructor Detail

 o EvaluationUtils
public EvaluationUtils()

Method Detail

 o setSeed
public void setSeed(int seed)
          Sets the seed for randomization during cross-validation
 o getSeed
public int getSeed()
          Gets the seed for randomization during cross-validation
 o getCVPredictions
public FastVector getCVPredictions(DistributionClassifier classifier,
                                   Instances data,
                                   int numFolds) throws java.lang.Exception
          Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
Parameters:
classifier - the DistributionClassifier to evaluate
data - the dataset
numFolds - the number of folds in the cross-validation.
Throws:
java.lang.Exception - if an error occurs
 o getTrainTestPredictions
public FastVector getTrainTestPredictions(DistributionClassifier classifier,
                                          Instances train,
                                          Instances test) throws java.lang.Exception
          Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
Parameters:
classifier - the DistributionClassifier to evaluate
train - the training dataset
test - the test dataset
Throws:
java.lang.Exception - if an error occurs
 o getTestPredictions
public FastVector getTestPredictions(DistributionClassifier classifier,
                                     Instances test) throws java.lang.Exception
          Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
Parameters:
classifier - the pre-trained DistributionClassifier to evaluate
test - the test dataset
Throws:
java.lang.Exception - if an error occurs
 o getPrediction
public Prediction getPrediction(DistributionClassifier classifier,
                                Instance test) throws java.lang.Exception
          Generate a single prediction for a test instance given the pre-trained classifier.
Parameters:
classifier - the pre-trained DistributionClassifier to evaluate
test - the test instance
Throws:
java.lang.Exception - if an error occurs

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