LocalNonnegativeMatrixFactorization (Carrot2 v3.17.0-SNAPSHOT API Documentation (JavaDoc))

java.lang.Object
- org.carrot2.matrix.factorization.LocalNonnegativeMatrixFactorization

All Implemented Interfaces:

IIterativeMatrixFactorization, IMatrixFactorization
```
public class LocalNonnegativeMatrixFactorization
extends Object
```
Performs matrix factorization using the Local Non-negative Matrix Factorization algorithm with minimization of the Kullback-Leibler divergence between A and UV' and multiplicative updating.

Field Summary

Fields
Modifier and Type	Field and Description
`protected DoubleMatrix2D`	`A` Input matrix
`protected double[]`	`aggregates` Sorting aggregates
`protected double`	`approximationError` Current approximation error
`protected double[]`	`approximationErrors` Approximation errors during subsequent iterations
`protected static int`	`DEFAULT_K`
`protected static int`	`DEFAULT_MAX_ITERATIONS`
`protected static boolean`	`DEFAULT_ORDERED`
`protected static ISeedingStrategy`	`DEFAULT_SEEDING_STRATEGY`
`protected static double`	`DEFAULT_STOP_THRESHOLD`
`protected int`	`iterationsCompleted` Iteration counter
`protected int`	`k` The desired number of base vectors
`protected int`	`maxIterations` The maximum number of iterations the algorithm is allowed to run
`protected boolean`	`ordered` Order base vectors according to their 'activity'?
`protected ISeedingStrategy`	`seedingStrategy` Seeding strategy
`protected double`	`stopThreshold` If the percentage decrease in approximation error becomes smaller than `stopThreshold`, the algorithm will stop.
`protected DoubleMatrix2D`	`U` Base vector result matrix
`protected DoubleMatrix2D`	`V` Coefficient result matrix

Constructor Summary

Constructors
Constructor and Description

LocalNonnegativeMatrixFactorization(DoubleMatrix2D A)
Creates the LocalNonnegativeMatrixFactorization object for matrix A.

Constructors
Constructor and Description
`LocalNonnegativeMatrixFactorization(DoubleMatrix2D A)` Creates the LocalNonnegativeMatrixFactorization object for matrix A.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`compute()` Computes the factorization.
`double[]`	`getAggregates()` Returns column aggregates for a sorted factorization, and `null` for an unsorted factorization.
`double`	`getApproximationError()` Returns approximation error achieved after the last iteration of the algorithm or -1 if the approximation error is not available.
`double[]`	`getApproximationErrors()`
`int`	`getIterationsCompleted()` Returns the number of iterations the algorithm has completed.
`int`	`getK()` Returns the number of base vectors k .
`int`	`getMaxIterations()` Returns the maximum number of iterations the algorithm is allowed to run.
`ISeedingStrategy`	`getSeedingStrategy()` Returns current `ISeedingStrategy`.
`double`	`getStopThreshold()` Returns the algorithms `stopThreshold`.
`DoubleMatrix2D`	`getU()` Returns the U matrix (base vectors matrix).
`DoubleMatrix2D`	`getV()` Returns the V matrix (coefficient matrix)
`boolean`	`isOrdered()` Returns `true` when the factorization is set to generate an ordered basis.
`protected void`	`order()` Orders U and V matrices according to the 'activity' of base vectors.
`void`	`setK(int k)` Sets the number of base vectors k .
`void`	`setMaxIterations(int maxIterations)` Sets the maximum number of iterations the algorithm is allowed to run.
`void`	`setOrdered(boolean ordered)` Set to `true` to generate an ordered basis.
`void`	`setSeedingStrategy(ISeedingStrategy seedingStrategy)` Sets new `ISeedingStrategy`.
`void`	`setStopThreshold(double stopThreshold)` Sets the algorithms `stopThreshold`.
`String`	`toString()`
`protected boolean`	`updateApproximationError()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.carrot2.matrix.factorization.IMatrixFactorization
getU, getV

- Field Detail
  - k
```
protected int k
```
    The desired number of base vectors
  - DEFAULT_K
```
protected static int DEFAULT_K
```
  - maxIterations
```
protected int maxIterations
```
    The maximum number of iterations the algorithm is allowed to run
  - DEFAULT_MAX_ITERATIONS
```
protected static final int DEFAULT_MAX_ITERATIONS
```
    See Also:
    
    Constant Field Values
  - stopThreshold
```
protected double stopThreshold
```
    If the percentage decrease in approximation error becomes smaller than stopThreshold, the algorithm will stop. Note: calculation of approximation error is quite costly. Setting the threshold to -1 turns off approximation error calculation and hence makes the algorithm do the maximum number of iterations.
  - DEFAULT_STOP_THRESHOLD
```
protected static double DEFAULT_STOP_THRESHOLD
```
  - seedingStrategy
```
protected ISeedingStrategy seedingStrategy
```
    Seeding strategy
  - DEFAULT_SEEDING_STRATEGY
```
protected static final ISeedingStrategy DEFAULT_SEEDING_STRATEGY
```
  - ordered
```
protected boolean ordered
```
    Order base vectors according to their 'activity'?
  - DEFAULT_ORDERED
```
protected static final boolean DEFAULT_ORDERED
```
    See Also:
    
    Constant Field Values
  - approximationError
```
protected double approximationError
```
    Current approximation error
  - approximationErrors
```
protected double[] approximationErrors
```
    Approximation errors during subsequent iterations
  - iterationsCompleted
```
protected int iterationsCompleted
```
    Iteration counter
  - aggregates
```
protected double[] aggregates
```
    Sorting aggregates
  - A
```
protected DoubleMatrix2D A
```
    Input matrix
  - U
```
protected DoubleMatrix2D U
```
    Base vector result matrix
  - V
```
protected DoubleMatrix2D V
```
    Coefficient result matrix
- Constructor Detail
  - LocalNonnegativeMatrixFactorization
```
public LocalNonnegativeMatrixFactorization(DoubleMatrix2D A)
```
    Creates the LocalNonnegativeMatrixFactorization object for matrix A. Before accessing results, perform computations by calling the compute()method.
    
    Parameters:
    
    A - matrix to be factorized
- Method Detail
  - compute
```
public void compute()
```
    Computes the factorization.
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - setK
```
public void setK(int k)
```
    Sets the number of base vectors k .
    
    Parameters:
    
    k - the number of base vectors
  - getK
```
public int getK()
```
    Returns the number of base vectors k .
  - updateApproximationError
```
protected boolean updateApproximationError()
```
    Returns:
    
    true if the decrease in the approximation error is smaller than the stopThreshold
  - order
```
protected void order()
```
    Orders U and V matrices according to the 'activity' of base vectors.
  - getSeedingStrategy
```
public ISeedingStrategy getSeedingStrategy()
```
    Returns current ISeedingStrategy.
  - setSeedingStrategy
```
public void setSeedingStrategy(ISeedingStrategy seedingStrategy)
```
    Sets new ISeedingStrategy.
  - getMaxIterations
```
public int getMaxIterations()
```
    Returns the maximum number of iterations the algorithm is allowed to run.
  - setMaxIterations
```
public void setMaxIterations(int maxIterations)
```
    Sets the maximum number of iterations the algorithm is allowed to run.
  - getStopThreshold
```
public double getStopThreshold()
```
    Returns the algorithms stopThreshold. If the percentage decrease in approximation error becomes smaller than stopThreshold, the algorithm will stop.
  - setStopThreshold
```
public void setStopThreshold(double stopThreshold)
```
    Sets the algorithms stopThreshold. If the percentage decrease in approximation error becomes smaller than stopThreshold, the algorithm will stop.
    Note: calculation of approximation error is quite costly. Setting the threshold to -1 turns off calculation of the approximation error and hence makes the algorithm do the maximum allowed number of iterations.
  - getApproximationError
```
public double getApproximationError()
```
    Description copied from interface: IIterativeMatrixFactorization
    
    Returns approximation error achieved after the last iteration of the algorithm or -1 if the approximation error is not available.
    
    Specified by:
    
    getApproximationError in interface IIterativeMatrixFactorization
    
    Returns:
    
    approximation error or -1
  - getApproximationErrors
```
public double[] getApproximationErrors()
```
  - getIterationsCompleted
```
public int getIterationsCompleted()
```
    Description copied from interface: IIterativeMatrixFactorization
    
    Returns the number of iterations the algorithm has completed.
    
    Specified by:
    
    getIterationsCompleted in interface IIterativeMatrixFactorization
    
    Returns:
    
    the number of iterations the algorithm has completed
  - isOrdered
```
public boolean isOrdered()
```
    Returns true when the factorization is set to generate an ordered basis.
  - setOrdered
```
public void setOrdered(boolean ordered)
```
    Set to true to generate an ordered basis.
  - getAggregates
```
public double[] getAggregates()
```
    Returns column aggregates for a sorted factorization, and null for an unsorted factorization.
  - getU
```
public DoubleMatrix2D getU()
```
    Description copied from interface: IMatrixFactorization
    
    Returns the U matrix (base vectors matrix).
    
    Specified by:
    
    getU in interface IMatrixFactorization
    
    Returns:
    
    U matrix
  - getV
```
public DoubleMatrix2D getV()
```
    Description copied from interface: IMatrixFactorization
    
    Returns the V matrix (coefficient matrix)
    
    Specified by:
    
    getV in interface IMatrixFactorization
    
    Returns:
    
    V matrix

Class LocalNonnegativeMatrixFactorization

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface org.carrot2.matrix.factorization.IMatrixFactorization

Field Detail

k

DEFAULT_K

maxIterations

DEFAULT_MAX_ITERATIONS

stopThreshold

DEFAULT_STOP_THRESHOLD

seedingStrategy

DEFAULT_SEEDING_STRATEGY

ordered

DEFAULT_ORDERED

approximationError

approximationErrors

iterationsCompleted

aggregates

A

U

V

Constructor Detail

LocalNonnegativeMatrixFactorization

Method Detail

compute

toString

setK

getK

updateApproximationError

order

getSeedingStrategy

setSeedingStrategy

getMaxIterations

setMaxIterations

getStopThreshold

setStopThreshold

getApproximationError

getApproximationErrors

getIterationsCompleted

isOrdered

setOrdered

getAggregates

getU

getV