es.upm.etsisi.cf4j.recommender.matrixFactorization

Class NMF

java.lang.Object

es.upm.etsisi.cf4j.recommender.Recommender

es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF

public class NMF
extends Recommender

Implements Lee, D. D., & Seung, H. S. (2001). Algorithms for non-negative matrix factorization. In Advances in neural information processing systems (pp. 556-562).

Field Summary

Fields

Modifier and Type	Field and Description
protected double[][]	h Item factors
protected int	numFactors Number of factors
protected int	numIters Number of iterations
protected double[][]	w User factors

Fields inherited from class es.upm.etsisi.cf4j.recommender.Recommender

datamodel

Constructor Summary

Constructors

Constructor and Description
NMF(DataModel datamodel, int numFactors, int numIters) Model constructor
NMF(DataModel datamodel, int numFactors, int numIters, long seed) Model constructor
NMF(DataModel datamodel, Map<String,Object> params) Model constructor from a Map containing the model's hyper-parameters values.

Method Summary

Modifier and Type	Method and Description
void	fit() Estimates model parameters given the hyper-parameters
int	getNumFactors() Get the number of factors of the model
int	getNumIters() Get the number of iterations
double	predict(int userIndex, int itemIndex) Computes a rating prediction
String	toString()

Methods inherited from class es.upm.etsisi.cf4j.recommender.Recommender

getDataModel, predict

Methods inherited from class java.lang.Object

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

Field Detail

w

protected final double[][] w

User factors

h

protected final double[][] h

Item factors

numFactors

protected final int numFactors

Number of factors

numIters

protected final int numIters

Number of iterations

Constructor Detail

NMF

public NMF(DataModel datamodel,
           Map<String,Object> params)

Model constructor from a Map containing the model's hyper-parameters values. Map object must contains the following keys:

• numFactors: int value with the number of latent factors.
• numIters:: int value with the number of iterations.
• seed (optional): random seed for random numbers generation. If missing, random value is used.

Parameters:

datamodel - DataModel instance

params - Model's hyper-parameters values

NMF

public NMF(DataModel datamodel,
           int numFactors,
           int numIters)

Model constructor

Parameters:

datamodel - DataModel instance

numFactors - Number of factors

numIters - Number of iterations

NMF

public NMF(DataModel datamodel,
           int numFactors,
           int numIters,
           long seed)

Model constructor

Parameters:

datamodel - DataModel instance

numFactors - Number of factors

numIters - Number of iterations

seed - Seed for random numbers generation

Method Detail

getNumFactors

public int getNumFactors()

Get the number of factors of the model

Returns:

Number of factors

getNumIters

public int getNumIters()

Get the number of iterations

Returns:

Number of iterations

fit

public void fit()

Description copied from class: Recommender

Estimates model parameters given the hyper-parameters

Specified by:

fit in class Recommender

predict

public double predict(int userIndex,
                      int itemIndex)

Description copied from class: Recommender

Computes a rating prediction

Specified by:

predict in class Recommender

Parameters:

userIndex - Index of the user in the array of Users of the DataModel instance

itemIndex - Index of the item in the array of Items of the DataModel instance

Returns:

Prediction

toString

public String toString()

Overrides:

toString in class Object