net.librec.recommender.ext

Class PersonalityDiagnosisRecommender

java.lang.Object

net.librec.recommender.AbstractRecommender

net.librec.recommender.ext.PersonalityDiagnosisRecommender

All Implemented Interfaces:

Recommender

public class PersonalityDiagnosisRecommender
extends AbstractRecommender

Related Work:

• A brief introduction to Personality Diagnosis

Author:

guoguibing and Keqiang Wang

Field Summary

Fields inherited from class net.librec.recommender.AbstractRecommender

conf, context, decay, earlyStop, globalMean, isBoldDriver, isRanking, itemMappingData, lastLoss, LOG, loss, maxRate, minRate, numItems, numRates, numUsers, ratingScale, recommendedList, testMatrix, topN, trainMatrix, userMappingData, validMatrix, verbose

Constructor Summary

Constructors

Constructor and Description
PersonalityDiagnosisRecommender()

Method Summary

Methods

Modifier and Type	Method and Description
protected double	gaussian(double x, double mu, double sigma)
protected double	predict(int userIdx, int itemIdx) predict a specific rating for user userIdx on item itemIdx.
protected void	setup() initialization
protected void	trainModel() train model

Methods inherited from class net.librec.recommender.AbstractRecommender

cleanup, evaluate, evaluateMap, getContext, getDataModel, getRecommendedList, isConverged, loadModel, predict, recommend, recommend, recommendRank, recommendRating, saveModel, setContext

Methods inherited from class java.lang.Object

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

Constructor Detail

PersonalityDiagnosisRecommender

public PersonalityDiagnosisRecommender()

Method Detail

setup

protected void setup()
              throws LibrecException

initialization

Overrides:

setup in class AbstractRecommender

Throws:

LibrecException - if error occurs

trainModel

protected void trainModel()
                   throws LibrecException

train model

Specified by:

trainModel in class AbstractRecommender

Throws:

LibrecException - if error occurs

predict

protected double predict(int userIdx,
             int itemIdx)
                  throws LibrecException

predict a specific rating for user userIdx on item itemIdx.

Specified by:

predict in class AbstractRecommender

Parameters:

userIdx - user index

itemIdx - item index

Returns:

predictive rating for user userIdx on item itemIdx

Throws:

LibrecException - if error occurs

gaussian

protected double gaussian(double x,
              double mu,
              double sigma)

Parameters:

x - input value

mu - mean of normal distribution

sigma - standard deviation of normation distribution

Returns:

a gaussian value with mean mu and standard deviation sigma;