Module es.upm.fi.cig.multictbnc

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

Class TestDatasetBinaryRelevanceMethod

java.lang.Object

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

es.upm.fi.cig.multictbnc.performance.TestDatasetBinaryRelevanceMethod

public class TestDatasetBinaryRelevanceMethod
extends ValidationMethod

Implements a validation method for evaluating CTBNCs using a test. This method involves training separate models for each class variable and then combining their predictions to evaluate the overall performance of the model on the test dataset.

Constructor Summary

Constructors

Constructor	Description
TestDatasetBinaryRelevanceMethod(DatasetReader trainingDatasetReader, DatasetReader testDatasetReader, boolean estimateProbabilities)	Constructor that receives the dataset readers and configuration.

Method Summary

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

TestDatasetBinaryRelevanceMethod

public TestDatasetBinaryRelevanceMethod(DatasetReader trainingDatasetReader,
 DatasetReader testDatasetReader,
 boolean estimateProbabilities)
                                 throws UnreadDatasetException

Constructor that receives the dataset readers and configuration.

Parameters:

trainingDatasetReader - reader for the training dataset

testDatasetReader - reader for the test dataset

estimateProbabilities - flag indicating if probabilities should be estimated

Throws:

UnreadDatasetException - if the dataset cannot be read

Method Details

evaluate

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

Description copied from class: ValidationMethod

Evaluates the performance of the specified model and returns the results.

Specified by:

evaluate in class ValidationMethod

Parameters:

model - model to evaluate

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

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