org.aisb.bio.tools
Class EuclideanMeanClassifier

java.lang.Object
  org.aisb.bio.tools.Classifier
      org.aisb.bio.tools.EuclideanMeanClassifier

public class EuclideanMeanClassifier

extends Classifier

This classifier just figures out the mean of all the features in the training data, and then classifies data by calculating the Euclidean distance between the data to be classified and the means for the categories. Pretty simple stuff.

In this particular case, the "data" must be a vector (array) of doubles. Each elemenet of data must be of the same length, but we don't need to care what that length is.

Author:

Doug DeJulio

Constructor Summary

EuclideanMeanClassifier()

Method Summary

java.lang.String	classify(java.lang.Object testData) Given a trained classifier, use it to classify a piece of data.
void	finishTraining()
void	startTraining()
void	train(java.lang.String label, java.lang.Object trainingDatum) Feed training data to the classifier.

Methods inherited from class java.lang.Object

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

Constructor Detail

EuclideanMeanClassifier

public EuclideanMeanClassifier()

Method Detail

startTraining

public void startTraining()

Overrides:

startTraining in class Classifier

finishTraining

public void finishTraining()

Overrides:

finishTraining in class Classifier

train

public void train(java.lang.String label,
                  java.lang.Object trainingDatum)

Description copied from class: Classifier

Feed training data to the classifier.

Specified by:

train in class Classifier

Parameters:

label - The label that this unit of data has.

trainingDatum - The data to be used for classification.

classify

public java.lang.String classify(java.lang.Object testData)

Description copied from class: Classifier

Given a trained classifier, use it to classify a piece of data.

Specified by:

classify in class Classifier

Parameters:

testData - The data to be classified.

Returns:

The label the classifier assigns to this data.