edu.ucla.sspace.matrix.factorization

Class NonNegativeMatrixFactorizationOPL

java.lang.Object

edu.ucla.sspace.matrix.factorization.NonNegativeMatrixFactorizationOPL

All Implemented Interfaces:

MatrixFactorization

public class NonNegativeMatrixFactorizationOPL
extends Object
implements MatrixFactorization

A simple implementation of Non-Negative Matrix Factorization. This is an implementation of the Oblique Projected Landweber Method explained in

R Zdunek and A. Cichocki, (2008), "Fast Nonnegative Matrix Factorization Algorithms Using Projected Gradient Approaches for Lage-Scale Problems," Intell. Neuroscience, vol. 2008, here

NOTE: Does not work yet. Returns 0 matrices.

Author:

Keith Stevens

Field Summary

Fields

Modifier and Type	Field and Description
static String	DEFAULT_ITERATIONS By default, use this many iterations.
static String	ITERATIONS The System Property used to define the number of gradient iterations used when decomposing a matrix.
static String	PROPERTY_PREFIX The base property prefix.

Constructor Summary

Constructors

Constructor and Description
NonNegativeMatrixFactorizationOPL() Instantiates a new NonNegativeMatrixFactorizationOPL that uses the system default Properties to determnine the number of iterations to use when decomposing matrices.
NonNegativeMatrixFactorizationOPL(int numIterations) Instantiates a new NonNegativeMatrixFactorizationOPL instance which will use numIterations to compute the decomposed matrices.
NonNegativeMatrixFactorizationOPL(Properties props) Instantiates a new NonNegativeMatrixFactorizationOPL that uses the provided Properties to determnine the number of iterations to use when decomposing matrices.

Method Summary

Methods

Modifier and Type	Method and Description
Matrix	classFeatures() Returns the latent class by feature Matrix.
Matrix	dataClasses() Returns the data point by latent class Matrix.
void	factorize(MatrixFile mFile, int numDimensions) Factorizes the MatrixFile m.
void	factorize(SparseMatrix m, int numDimensions) Factorizes the SparseMatrix m.
MatrixBuilder	getBuilder() Returns a MatrixBuilder that is optimized for MatrixFiles that will be processed by this MatrixFactorization algorithm.
static void	initialize(Matrix m) Initializes every value in m to be a random value between 0 and 1, inclusive.
static void	makeNonZero(Matrix m) Sets any negative values of m to zero.

Methods inherited from class java.lang.Object

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

Field Detail

PROPERTY_PREFIX

public static final String PROPERTY_PREFIX

The base property prefix.

See Also:

Constant Field Values

ITERATIONS

public static final String ITERATIONS

The System Property used to define the number of gradient iterations used when decomposing a matrix.

See Also:

Constant Field Values

DEFAULT_ITERATIONS

public static final String DEFAULT_ITERATIONS

By default, use this many iterations.

See Also:

Constant Field Values

Constructor Detail

NonNegativeMatrixFactorizationOPL

public NonNegativeMatrixFactorizationOPL()

Instantiates a new NonNegativeMatrixFactorizationOPL that uses the system default Properties to determnine the number of iterations to use when decomposing matrices.

NonNegativeMatrixFactorizationOPL

public NonNegativeMatrixFactorizationOPL(Properties props)

Instantiates a new NonNegativeMatrixFactorizationOPL that uses the provided Properties to determnine the number of iterations to use when decomposing matrices.

NonNegativeMatrixFactorizationOPL

public NonNegativeMatrixFactorizationOPL(int numIterations)

Instantiates a new NonNegativeMatrixFactorizationOPL instance which will use numIterations to compute the decomposed matrices.

Method Detail

factorize

public void factorize(MatrixFile mFile,
             int numDimensions)

Factorizes the MatrixFile m. If m is of size MxN, this will generate two matrices: one of size MxnumDimensions and one of size numDimensionsxN. This method must be called before calling dataClasses and classFeatures.

Specified by:

factorize in interface MatrixFactorization

factorize

public void factorize(SparseMatrix m,
             int numDimensions)

Factorizes the SparseMatrix m. If m is of size MxN, this will generate two matrices: one of size MxnumDimensions and one of size numDimensionsxN. This method must be called before calling dataClasses and classFeatures.

Specified by:

factorize in interface MatrixFactorization

dataClasses

public Matrix dataClasses()

Returns the data point by latent class Matrix. This matrix represents the degree by which each data point can be explained by the discovered latent classes. Actual interpretations of the latent classes depends on the actual algorithm used. This Matrix can be used as a reduced representation of the data points themselves.

Specified by:

dataClasses in interface MatrixFactorization

classFeatures

public Matrix classFeatures()

Returns the latent class by feature Matrix. This matrix represents the degree by which each feature affects each latent class. Actual interpretations of this interaction depends on the actual algorithm used. This Matrix can be used as a reduced representation of the features.

Specified by:

classFeatures in interface MatrixFactorization

getBuilder

public MatrixBuilder getBuilder()

Returns a MatrixBuilder that is optimized for MatrixFiles that will be processed by this MatrixFactorization algorithm.

Specified by:

getBuilder in interface MatrixFactorization

makeNonZero

public static void makeNonZero(Matrix m)

Sets any negative values of m to zero.

initialize

public static void initialize(Matrix m)

Initializes every value in m to be a random value between 0 and 1, inclusive.