hex.glm

Class ComputationState

java.lang.Object

hex.glm.ComputationState

public final class ComputationState
extends java.lang.Object

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ComputationState.GLMSubsetGinfo

Field Summary

Fields

Modifier and Type	Field and Description
boolean	_lsNeeded

Constructor Summary

Constructors

Constructor and Description
ComputationState(water.Job job, GLMModel.GLMParameters parms, DataInfo dinfo, GLM.BetaConstraint bc, int nclasses)

Method Summary

Methods

Modifier and Type	Method and Description
GLM.BetaConstraint	activeBC()
DataInfo	activeData()
DataInfo	activeDataMultinomial()
DataInfo	activeDataMultinomial(int c)
protected void	applyStrongRules(double lambdaNew, double lambdaOld) Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
protected int	applyStrongRulesMultinomial_old(double lambdaNew, double lambdaOld) Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
protected void	applyStrongRulesMultinomial(double lambdaNew, double lambdaOld) Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
double[]	beta()
double[]	betaMultinomial()
double[]	betaMultinomial(int c, double[] beta)
protected boolean	checkKKTs()
protected boolean	checkKKTsMultinomial()
boolean	converged()
double	deviance()
void	dropActiveData()
double[]	expandBeta(double[] beta)
GLM.GLMGradientInfo	ginfo()
ComputationState.GLMSubsetGinfo	ginfoMultinomial(int c)
GLM.GLMGradientSolver	gslvr()
OptimizationUtils.GradientSolver	gslvrMultinomial(int c)
double	l1pen()
double	l2pen()
double	lambda()
double	likelihood()
double	objective()
double	objective(double[] beta, double likelihood)
int[]	removeCols(int[] cols)
void	setActiveClass(int activeClass)
void	setBC(GLM.BetaConstraint bc)
void	setBetaMultinomial(int c, double[] beta, double[] bc)
void	setLambda(double lambda)
void	setLambdaMax(double lmax)
java.lang.String	toString()
protected double	updateState(double[] beta, double likelihood)
protected double	updateState(double[] beta, GLM.GLMGradientInfo ginfo)

Methods inherited from class java.lang.Object

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

Field Detail

_lsNeeded

public boolean _lsNeeded

Constructor Detail

ComputationState

public ComputationState(water.Job job,
                GLMModel.GLMParameters parms,
                DataInfo dinfo,
                GLM.BetaConstraint bc,
                int nclasses)

Parameters:

nclasses - - number of classes for multinomial, 1 for everybody else

Method Detail

gslvr

public GLM.GLMGradientSolver gslvr()

lambda

public double lambda()

setLambdaMax

public void setLambdaMax(double lmax)

setLambda

public void setLambda(double lambda)

beta

public double[] beta()

ginfo

public GLM.GLMGradientInfo ginfo()

activeBC

public GLM.BetaConstraint activeBC()

likelihood

public double likelihood()

activeData

public DataInfo activeData()

activeDataMultinomial

public DataInfo activeDataMultinomial()

dropActiveData

public void dropActiveData()

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

l1pen

public double l1pen()

l2pen

public double l2pen()

applyStrongRules

protected void applyStrongRules(double lambdaNew,
                    double lambdaOld)

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

activeDataMultinomial

public DataInfo activeDataMultinomial(int c)

betaMultinomial

public double[] betaMultinomial()

betaMultinomial

public double[] betaMultinomial(int c,
                       double[] beta)

ginfoMultinomial

public ComputationState.GLMSubsetGinfo ginfoMultinomial(int c)

setBC

public void setBC(GLM.BetaConstraint bc)

setActiveClass

public void setActiveClass(int activeClass)

deviance

public double deviance()

gslvrMultinomial

public OptimizationUtils.GradientSolver gslvrMultinomial(int c)

setBetaMultinomial

public void setBetaMultinomial(int c,
                      double[] beta,
                      double[] bc)

applyStrongRulesMultinomial_old

protected int applyStrongRulesMultinomial_old(double lambdaNew,
                                  double lambdaOld)

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

Returns:

indices of expected active predictors.

applyStrongRulesMultinomial

protected void applyStrongRulesMultinomial(double lambdaNew,
                               double lambdaOld)

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

checkKKTsMultinomial

protected boolean checkKKTsMultinomial()

checkKKTs

protected boolean checkKKTs()

removeCols

public int[] removeCols(int[] cols)

objective

public double objective()

objective

public double objective(double[] beta,
               double likelihood)

updateState

protected double updateState(double[] beta,
                 double likelihood)

converged

public boolean converged()

updateState

protected double updateState(double[] beta,
                 GLM.GLMGradientInfo ginfo)

expandBeta

public double[] expandBeta(double[] beta)