hex.glm

Class Gram

java.lang.Object

water.Iced<Gram>

hex.glm.Gram

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, water.Freezable

public final class Gram
extends water.Iced<Gram>

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Gram.Cholesky
static class	Gram.GramTask Task to compute gram matrix normalized by the number of observations (not counting rows with NAs).
static class	Gram.InPlaceCholesky
static class	Gram.NonSPDMatrixException

Field Summary

Fields

Modifier and Type	Field and Description
double	_diagAdded
int	_diagN
double[][]	_xx

Constructor Summary

Constructors

Constructor and Description
Gram()
Gram(Gram g)
Gram(int N, int diag, int dense, int sparse, boolean hasIntercept)

Method Summary

Methods

Modifier and Type	Method and Description
void	add(Gram grm)
void	addDiag(double d)
void	addDiag(double d, boolean add2Intercept)
void	addRow(double[] x, int catN, int[] catIndexes, double w)
Gram.Cholesky	cholesky(Gram.Cholesky chol)
Gram.Cholesky	cholesky(Gram.Cholesky chol, boolean parallelize, java.lang.String id) Compute the cholesky decomposition.
double	diagAvg()
double	diagMin()
int	fullN()
double[][]	getDenseXX()
double[][]	getXX()
boolean	hasNaNsOrInfs()
void	mul(double x)
double[]	mul(double[] x)
void	mul(double[] x, double[] res)
double	sparseness()
java.lang.String	toString()

Methods inherited from class water.Iced

clone, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, write_impl, write, writeExternal, writeHTML_impl, writeHTML, writeJSON_impl, writeJSON

Methods inherited from class java.lang.Object

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

Field Detail

_xx

public double[][] _xx

_diagN

public final int _diagN

_diagAdded

public double _diagAdded

Constructor Detail

Gram

public Gram()

Gram

public Gram(int N,
    int diag,
    int dense,
    int sparse,
    boolean hasIntercept)

Gram

public Gram(Gram g)

Method Detail

fullN

public final int fullN()

addDiag

public void addDiag(double d)

addDiag

public void addDiag(double d,
           boolean add2Intercept)

sparseness

public double sparseness()

diagAvg

public double diagAvg()

diagMin

public double diagMin()

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

cholesky

public Gram.Cholesky cholesky(Gram.Cholesky chol)

cholesky

public Gram.Cholesky cholesky(Gram.Cholesky chol,
                     boolean parallelize,
                     java.lang.String id)

Compute the cholesky decomposition. In case our gram starts with diagonal submatrix of dimension N, we exploit this fact to reduce the complexity of the problem. We use the standard decomposition of the cholesky factorization into submatrices. We split the Gram into 3 regions (4 but we only consider lower diagonal, sparse means diagonal region in this context): diagonal diagonal*dense dense*dense Then we can solve the cholesky in 3 steps: 1. We solve the diagnonal part right away (just do the sqrt of the elements). 2. The diagonal*dense part is simply divided by the sqrt of diagonal. 3. Compute Cholesky of dense*dense - outer product of cholesky of diagonal*dense computed in previous step

Parameters:

chol -

Returns:

getXX

public double[][] getXX()

getDenseXX

public double[][] getDenseXX()

add

public void add(Gram grm)

hasNaNsOrInfs

public final boolean hasNaNsOrInfs()

addRow

public final void addRow(double[] x,
          int catN,
          int[] catIndexes,
          double w)

mul

public void mul(double x)

mul

public double[] mul(double[] x)

mul

public void mul(double[] x,
       double[] res)