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

Constructor Summary

Constructors

Constructor and Description
ComputationState(water.Key jobKey, 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(int c)
protected int	applyStrongRules() Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
protected int	applyStrongRulesMultinomial() Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
double[]	beta()
double[]	betaMultinomial(int c)
protected boolean	checkKKTs()
protected boolean	checkKKTsMultinomial()
boolean	converged()
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	objVal()
double	previousLambda()
int[]	removeCols(int[] cols)
void	setBC(GLM.BetaConstraint bc)
void	setBetaMultinomial(int c, double[] b, ComputationState.GLMSubsetGinfo ginfo)
void	setLambda(double lambda)
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

Constructor Detail

ComputationState

public ComputationState(water.Key jobKey,
                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()

previousLambda

public double previousLambda()

setLambda

public void setLambda(double lambda)

beta

public double[] beta()

ginfo

public GLM.GLMGradientInfo ginfo()

activeBC

public GLM.BetaConstraint activeBC()

objVal

public double objVal()

likelihood

public double likelihood()

activeData

public DataInfo activeData()

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 int applyStrongRules()

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

Returns:

indices of expected active predictors.

activeDataMultinomial

public DataInfo activeDataMultinomial(int c)

betaMultinomial

public double[] betaMultinomial(int c)

ginfoMultinomial

public ComputationState.GLMSubsetGinfo ginfoMultinomial(int c)

setBC

public void setBC(GLM.BetaConstraint bc)

gslvrMultinomial

public OptimizationUtils.GradientSolver gslvrMultinomial(int c)

setBetaMultinomial

public void setBetaMultinomial(int c,
                      double[] b,
                      ComputationState.GLMSubsetGinfo ginfo)

applyStrongRulesMultinomial

protected int applyStrongRulesMultinomial()

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

Returns:

indices of expected active predictors.

checkKKTsMultinomial

protected boolean checkKKTsMultinomial()

checkKKTs

protected boolean checkKKTs()

removeCols

public int[] removeCols(int[] cols)

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)