emolib.classifier.heuristic
Class ThreeIntervalsKE

java.lang.Object
  emolib.util.proc.TextDataProcessor
      emolib.classifier.Classifier
          emolib.classifier.heuristic.ThreeIntervalsKE

All Implemented Interfaces:

Configurable, DataProcessor

public class ThreeIntervalsKE
extends Classifier

The ThreeIntervalsKE is a heuristic rules-based classifier operating on the circumplex with sentiments.

This class works exactly as the Five Intervals heuristic rules classifier, but displays the sentiment corresponding to the predicted emotion.

Author:

Alexandre Trilla (atrilla@salle.url.edu)

See Also:

FiveIntervalsKE

Constructor Summary

ThreeIntervalsKE()
Main constructor of this neuristic rules classifier.

Method Summary

java.lang.String	getCategory(FeatureBox inputFeatures) The function that decides the most appropriate emotional category.
void	load(java.lang.String path) Generic function to load a previously saved classifier.
void	save(java.lang.String path) Generic method to save the fully fledged classifier into a given file path.
void	trainingProcedure() Void method to train required by the Classifier class.

Methods inherited from class emolib.classifier.Classifier

applyClassification, getData, getListOfExampleCategories, getListOfExampleFeatures, initialize, inputTrainingExample, newProperties, register, resetExamples, train

Methods inherited from class emolib.util.proc.TextDataProcessor

flush, getName, getPredecessor, setPredecessor, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

ThreeIntervalsKE

public ThreeIntervalsKE()

Main constructor of this neuristic rules classifier.

Method Detail

getCategory

public java.lang.String getCategory(FeatureBox inputFeatures)

Description copied from class: Classifier

The function that decides the most appropriate emotional category. This is required for any classifier. The classifier in question has to previously run any training algorithm in order to provide the required prediction.

Specified by:

getCategory in class Classifier

Parameters:

inputFeatures - The input emotional features.

Returns:

The most appropriate emotional category.

trainingProcedure

public void trainingProcedure()

Void method to train required by the Classifier class.

Specified by:

trainingProcedure in class Classifier

save

public void save(java.lang.String path)

Description copied from class: Classifier

Generic method to save the fully fledged classifier into a given file path. It is recommended to use a plain text file (such as XML) to save the classifier's configuration since it's readable directly.

Specified by:

save in class Classifier

Parameters:

path - The file path to save the classifier.

load

public void load(java.lang.String path)

Description copied from class: Classifier

Generic function to load a previously saved classifier. This function should be consistent with the design followed in the saving procedure.

Specified by:

load in class Classifier

Parameters:

path - The path of the file which contains the previously saved classifier.