BNMF (CF4J 2.1.0 API Documentation)

java.lang.Object
- es.upm.etsisi.cf4j.recommender.Recommender
- - es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF

```
public class BNMF
extends Recommender
```
Implements Hernando, A., Bobadilla, J., & Ortega, F. (2016). A non negative matrix factorization for collaborative filtering recommender systems on a Bayesian probabilistic model. Knowledge-Based Systems, 97, 188-202.

Field Summary

Fields
Modifier and Type	Field and Description
`protected double[][]`	`a` User factors
`protected double`	`alpha` This hyper-parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes.
`protected double[][]`	`b` Item factors
`protected double`	`beta` This hyper-parameter represents the amount of evidence that the algorithm requires to deduce that a group of users likes an item.
`protected static double`	`DEFAULT_R`
`protected double[][]`	`epsilonMinus` Epsilon- parameters
`protected double[][]`	`epsilonPlus` Epsilon+ parameters
`protected double[][]`	`gamma` Gamma parameters
`protected int`	`numFactors` Number of factors
`protected int`	`numIters` Number of iterations
`protected double`	`r` Hyper-parameter of the binomial distribution.

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

Constructor Summary

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

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`fit()` Estimates model parameters given the hyper-parameters
`double`	`getAlpha()` Get the alpha value
`double`	`getBeta()` Get the beta value
`double[]`	`getEpsilonMinus(int itemIndex)` Get the epsilon- vector of an item
`double[]`	`getEpsilonPlus(int itemIndex)` Get the epsilon+ vector of an item
`double[]`	`getGamma(int userIndex)` Get the gamma vector of an user
`double[]`	`getItemFactors(int itemIndex)` Get the latent factors vector of an item (bi)
`int`	`getNumFactors()` Get the number of factors of the model
`int`	`getNumIters()` Get the number of iterations
`double`	`getR()` Get the r value
`double[]`	`getUserFactors(int userIndex)` Get the latent factors vector of a user (au)
`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
  - DEFAULT_R
```
protected static final double DEFAULT_R
```
    See Also:
    
    Constant Field Values
  - a
```
protected double[][] a
```
    User factors
  - b
```
protected double[][] b
```
    Item factors
  - gamma
```
protected double[][] gamma
```
    Gamma parameters
  - epsilonPlus
```
protected double[][] epsilonPlus
```
    Epsilon+ parameters
  - epsilonMinus
```
protected double[][] epsilonMinus
```
    Epsilon- parameters
  - alpha
```
protected final double alpha
```
    This hyper-parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes.
  - beta
```
protected final double beta
```
    This hyper-parameter represents the amount of evidence that the algorithm requires to deduce that a group of users likes an item.
  - r
```
protected final double r
```
    Hyper-parameter of the binomial distribution.
  - numFactors
```
protected final int numFactors
```
    Number of factors
  - numIters
```
protected final int numIters
```
    Number of iterations
- Constructor Detail
  - BNMF
```
public BNMF(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.
    - alpha: double value with the alpha hyper-parameter. This value is related to the possibility of obtaining overlapping groups of users sharing the same tastes.
    - beta: double value with the beta hyper-parameter. This value represents the amount of evidences that the algorithm requires to deduce that a group of users likes an item.
    - seed (optional): random seed for generating random numbers. If missing, random value is used.
    Parameters:
    
    datamodel - DataModel instance
    
    params - Model's hyper-parameters values
  - BNMF
```
public BNMF(DataModel datamodel,
            int numFactors,
            int numIters,
            double alpha,
            double beta)
```
    Model constructor
    
    Parameters:
    
    datamodel - DataModel instance
    
    numFactors - Number of factors
    
    numIters - Number of iterations
    
    alpha - This parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes
    
    beta - Amount of evidences that the algorithm requires to deduce that a group of users likes an item
  - BNMF
```
public BNMF(DataModel datamodel,
            int numFactors,
            int numIters,
            double alpha,
            double beta,
            long seed)
```
    Model constructor
    
    Parameters:
    
    datamodel - DataModel instance
    
    numFactors - Number of factors
    
    numIters - Number of iterations
    
    alpha - This parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes
    
    beta - Amount of evidences that the algorithm requires to deduce that a group of users likes an item
    
    seed - Seed for random numbers generation
  - BNMF
```
public BNMF(DataModel datamodel,
            int numFactors,
            int numIters,
            double alpha,
            double beta,
            double r,
            long seed)
```
    Model constructor
    
    Parameters:
    
    datamodel - DataModel instance
    
    numFactors - Number of factors
    
    numIters - Number of iterations
    
    alpha - This parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes
    
    beta - Amount of evidences that the algorithm requires to deduce that a group of users likes an item
    
    r - Parameter of the binomial distribution (fixed to 4)
    
    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
  - getAlpha
```
public double getAlpha()
```
    Get the alpha value
    
    Returns:
    
    Alpha value
  - getBeta
```
public double getBeta()
```
    Get the beta value
    
    Returns:
    
    Beta value
  - getR
```
public double getR()
```
    Get the r value
    
    Returns:
    
    r value
  - getGamma
```
public double[] getGamma(int userIndex)
```
    Get the gamma vector of an user
    
    Parameters:
    
    userIndex - user index
    
    Returns:
    
    User's gamma vector
  - getEpsilonPlus
```
public double[] getEpsilonPlus(int itemIndex)
```
    Get the epsilon+ vector of an item
    
    Parameters:
    
    itemIndex - item index
    
    Returns:
    
    Item's epsilon+ vector
  - getEpsilonMinus
```
public double[] getEpsilonMinus(int itemIndex)
```
    Get the epsilon- vector of an item
    
    Parameters:
    
    itemIndex - item index
    
    Returns:
    
    Item's epsilon- vector
  - getUserFactors
```
public double[] getUserFactors(int userIndex)
```
    Get the latent factors vector of a user (au)
    
    Parameters:
    
    userIndex - User
    
    Returns:
    
    Latent factors vector
  - getItemFactors
```
public double[] getItemFactors(int itemIndex)
```
    Get the latent factors vector of an item (bi)
    
    Parameters:
    
    itemIndex - User
    
    Returns:
    
    Latent factors vector
  - 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

Class BNMF

Field Summary

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

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Object

Field Detail

DEFAULT_R

a

b

gamma

epsilonPlus

epsilonMinus

alpha

beta

r

numFactors

numIters

Constructor Detail

BNMF

BNMF

BNMF

BNMF

Method Detail

getNumFactors

getNumIters

getAlpha

getBeta

getR

getGamma

getEpsilonPlus

getEpsilonMinus

getUserFactors

getItemFactors

fit

predict

toString