emolib.classifier.machinelearning
Class NearestCentroid

java.lang.Object
  extended by emolib.util.proc.TextDataProcessor
      extended by emolib.classifier.Classifier
          extended by emolib.classifier.machinelearning.NearestCentroid
All Implemented Interfaces:
Configurable, DataProcessor

public class NearestCentroid
extends Classifier

The NearestCentroid is a Rocchio classifier operating in the circumplex.

Once this classifier is fed with a sensible amount of examples for each class, the arithmetic mean of each emotional dimension is computed in order to provide the centroid corresponding to the class. The core of this classifier is based on a 1-NN where the examples are the centroids of the classes.

The NearestCentroid class includes a main method to train the classifier for a future use. Its training dataset is a plain text file where each row represents a training instance. The first numbers indicate the emotional dimensions while the last one represents the affective category.

For more information about this classifier, please refer to (Trilla and Alías, 2009).

--
(Trilla and Alías, 2009) Trilla, A. and Alías, F., "Sentiment classification in English from sentence-level annotations of emotions regarding models of affect", In Proceedings of the 10th Annual Conference of the International Speech Communication Association (Interspeech 2009) (ISSN: 1990-9772), pp. 516-519, 2009, September, Brighton, UK.

Author:
Alexandre Trilla (atrilla@salle.url.edu)
See Also:
KNearestNeighbour

Field Summary
static java.lang.String PROP_EXTERNAL_FILE
          Property to indicate a pre-trained classifier.
static java.lang.String PROP_NUM_EMO_DIMS
          Property to determine the number of emotional dimensions the NearestCentroid deals with.
 
Constructor Summary
NearestCentroid()
          Main constructor of this classifier.
 
Method Summary
 java.lang.String getCategory(FeatureBox inputFeatures)
          The function that decides the most appropriate emotional category.
 void initialize()
          Method to initialize the Classifier.
 void load(java.lang.String path)
          Generic function to load a previously saved classifier.
static void main(java.lang.String[] args)
          Main method to train the NearestCentroid classifier.
 void newProperties(PropertySheet ps)
          This method is called when this configurable component has new data.
 void printSynopsis()
          Prints the synopsis.
 void register(java.lang.String name, Registry registry)
          Register my properties.
 void resetExamples()
          Method to reset the classifier and flush the training examples.
 void save(java.lang.String path)
          Generic method to save the fully fledged classifier into a given file path.
 void setNumberOfEmotionalDimensions(int numDims)
          Method to set the number of emotional dimensions.
 void trainingProcedure()
          Generic training procedure.
 
Methods inherited from class emolib.classifier.Classifier
applyClassification, getData, getListOfExampleCategories, getListOfExampleFeatures, inputTrainingExample, 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
 

Field Detail

PROP_NUM_EMO_DIMS

public static final java.lang.String PROP_NUM_EMO_DIMS
Property to determine the number of emotional dimensions the NearestCentroid deals with.

See Also:
Constant Field Values

PROP_EXTERNAL_FILE

public static final java.lang.String PROP_EXTERNAL_FILE
Property to indicate a pre-trained classifier.

See Also:
Constant Field Values
Constructor Detail

NearestCentroid

public NearestCentroid()
Main constructor of this classifier.

Method Detail

register

public void register(java.lang.String name,
                     Registry registry)
              throws PropertyException
Description copied from interface: Configurable
Register my properties. This method is called once early in the time of the component, shortly after the component is constructed. This component should register any configuration properties that it needs to register. If this configurable extends another configurable, super.register should also be called

Specified by:
register in interface Configurable
Overrides:
register in class Classifier
Parameters:
name - the name of the component
registry - the registry for this component
Throws:
PropertyException

newProperties

public void newProperties(PropertySheet ps)
                   throws PropertyException
Description copied from interface: Configurable
This method is called when this configurable component has new data. The component should first validate the data. If it is bad the component should return false. If the data is good, the component should record the the data internally and return true.

Specified by:
newProperties in interface Configurable
Overrides:
newProperties in class Classifier
Parameters:
ps - a property sheet holding the new data
Throws:
PropertyException - if there is a problem with the properties.

initialize

public void initialize()
Method to initialize the Classifier.

Specified by:
initialize in interface DataProcessor
Overrides:
initialize in class Classifier

setNumberOfEmotionalDimensions

public void setNumberOfEmotionalDimensions(int numDims)
Method to set the number of emotional dimensions.

Parameters:
numDims - The number of emotional dimensions.

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()
Description copied from class: Classifier
Generic training procedure. It trains the classifier in question with the input training examples.

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.

resetExamples

public void resetExamples()
Description copied from class: Classifier
Method to reset the classifier and flush the training examples. This method only makes sense if the classifier in question is trainable and already has some training examples.

Overrides:
resetExamples in class Classifier

main

public static void main(java.lang.String[] args)
                 throws java.lang.Exception
Main method to train the NearestCentroid classifier.

Throws:
java.lang.Exception

printSynopsis

public void printSynopsis()
Prints the synopsis.