Module es.upm.fi.cig.multictbnc

Package es.upm.fi.cig.multictbnc.performance

Class CrossValidationBinaryRelevanceMethod

java.lang.Object

es.upm.fi.cig.multictbnc.performance.ValidationMethod

es.upm.fi.cig.multictbnc.performance.CrossValidationBinaryRelevanceMethod

public class CrossValidationBinaryRelevanceMethod
extends ValidationMethod

Implements a cross-validation method used to learn one CTBNC for each class variable and merge the results.

Constructor Summary

Constructors

Constructor	Description
CrossValidationBinaryRelevanceMethod(DatasetReader datasetReader, int folds, boolean estimateProbabilities, boolean shuffle, long seed)	Constructor for cross-validation method.

Method Summary

Modifier and Type	Method	Description
Map<String,Double>	evaluate(MultiCTBNC<?,?> model)	Evaluates the performance of the specified model using cross-validation.
Map<String,Double>	evaluate(MultiCTBNC<?,?> model, double preprocessingExecutionTime)	Evaluates the performance of the specified model and returns the results.

Methods inherited from class es.upm.fi.cig.multictbnc.performance.ValidationMethod

displayModel, displayResults, setWriter

Methods inherited from class java.lang.Object

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

Constructor Details

CrossValidationBinaryRelevanceMethod

public CrossValidationBinaryRelevanceMethod(DatasetReader datasetReader,
 int folds,
 boolean estimateProbabilities,
 boolean shuffle,
 long seed)
                                     throws UnreadDatasetException

Constructor for cross-validation method.

Parameters:

datasetReader - a DatasetReader to read the dataset

folds - number of folds

estimateProbabilities - true to estimate the probabilities of the class configurations, false otherwise

shuffle - true to shuffle the sequences, false otherwise

seed - seed used to shuffle the sequences

Throws:

UnreadDatasetException - if the provided dataset could not be read

Method Details

evaluate

public Map<String,Double> evaluate(MultiCTBNC<?,?> model)

Evaluates the performance of the specified model using cross-validation.

Specified by:

evaluate in class ValidationMethod

Parameters:

model - model to evaluate

Returns:

the results of the cross-validation in a Map

evaluate

public Map<String,Double> evaluate(MultiCTBNC<?,?> model,
 double preprocessingExecutionTime)
                            throws UnreadDatasetException,
ErroneousValueException

Description copied from class: ValidationMethod

Evaluates the performance of the specified model and returns the results. This method receives the execution time of previous tasks so it is add up to the total mean learning time.

Specified by:

evaluate in class ValidationMethod

Parameters:

model - model to evaluate

preprocessingExecutionTime - execution time of previous tasks

Returns:

results saved in a Map.

Throws:

UnreadDatasetException - if there was an error while reading a dataset

ErroneousValueException - if a provided parameter is erroneous for the requested task