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java.lang.Objectweka.classifiers.evaluation.EvaluationUtils
Contains utility functions for generating lists of predictions in various manners.
Constructor Summary | |
EvaluationUtils()
|
Method Summary | |
FastVector |
getCVPredictions(DistributionClassifier classifier,
Instances data,
int numFolds)
Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset. |
Prediction |
getPrediction(DistributionClassifier classifier,
Instance test)
Generate a single prediction for a test instance given the pre-trained classifier. |
int |
getSeed()
Gets the seed for randomization during cross-validation |
FastVector |
getTestPredictions(DistributionClassifier classifier,
Instances test)
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained. |
FastVector |
getTrainTestPredictions(DistributionClassifier classifier,
Instances train,
Instances test)
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set. |
void |
setSeed(int seed)
Sets the seed for randomization during cross-validation |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public EvaluationUtils()
Method Detail |
public void setSeed(int seed)
public int getSeed()
public FastVector getCVPredictions(DistributionClassifier classifier, Instances data, int numFolds) throws java.lang.Exception
classifier
- the DistributionClassifier to evaluatedata
- the datasetnumFolds
- the number of folds in the cross-validation.
java.lang.Exception
- if an error occurspublic FastVector getTrainTestPredictions(DistributionClassifier classifier, Instances train, Instances test) throws java.lang.Exception
classifier
- the DistributionClassifier to evaluatetrain
- the training datasettest
- the test dataset
java.lang.Exception
- if an error occurspublic FastVector getTestPredictions(DistributionClassifier classifier, Instances test) throws java.lang.Exception
classifier
- the pre-trained DistributionClassifier to evaluatetest
- the test dataset
java.lang.Exception
- if an error occurspublic Prediction getPrediction(DistributionClassifier classifier, Instance test) throws java.lang.Exception
classifier
- the pre-trained DistributionClassifier to evaluatetest
- the test instance
java.lang.Exception
- if an error occurs
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