hex

Class Distribution

java.lang.Object

water.Iced

hex.Distribution

All Implemented Interfaces:

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

public class Distribution
extends Iced

Distribution functions to be used by ML Algos

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Distribution.Family

Field Summary

Fields

Modifier and Type	Field and Description
Distribution.Family	distribution
static double	MAX
static double	MIN_LOG
double	tweediePower

Constructor Summary

Constructors

Constructor and Description
Distribution(Distribution.Family distribution) Short constructor for non-Tweedie distributions
Distribution(Distribution.Family distribution, double tweediePower) Constructor to be used for Tweedie (and if uncertain)

Method Summary

Methods

Modifier and Type	Method and Description
double	deviance(double w, double y, double f) Deviance of given distribution function at predicted value f
static double	exp(double x)
static java.lang.String	expString(java.lang.String x)
double	gammaDenom(double w, double y, double z, double f) Contribution to denominator for GBM's leaf node prediction
double	gammaNum(double w, double y, double z, double f) Contribution to numerator for GBM's leaf node prediction
double	gradient(double y, double f) Gradient of given distribution function at predicted value f
double	initFDenom(double w, double o) Contribution to denominator for initial value computation
double	initFNum(double w, double o, double y) Contribution to numerator for initial value computation
double	link(double f) Canonical link
double	linkInv(double f) Canonical link inverse
java.lang.String	linkInvString(java.lang.String f) String version of link inverse (for POJO scoring code generation)
static double	log(double x)

Methods inherited from class water.Iced

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

Methods inherited from class java.lang.Object

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

Field Detail

MIN_LOG

public static double MIN_LOG

MAX

public static double MAX

distribution

public final Distribution.Family distribution

tweediePower

public final double tweediePower

Constructor Detail

Distribution

public Distribution(Distribution.Family distribution)

Short constructor for non-Tweedie distributions

Parameters:

distribution -

Distribution

public Distribution(Distribution.Family distribution,
            double tweediePower)

Constructor to be used for Tweedie (and if uncertain)

Parameters:

distribution -

tweediePower - Tweedie Power

Method Detail

exp

public static double exp(double x)

log

public static double log(double x)

expString

public static java.lang.String expString(java.lang.String x)

deviance

public double deviance(double w,
              double y,
              double f)

Deviance of given distribution function at predicted value f

Parameters:

w - observation weight

y - (actual) response

f - (predicted) response in original response space

Returns:

value of gradient

gradient

public double gradient(double y,
              double f)

Gradient of given distribution function at predicted value f

Parameters:

y - (actual) response

f - (predicted) response in link space (including offset)

Returns:

value of gradient

link

public double link(double f)

Canonical link

Parameters:

f - value in original space, to be transformed to link space

Returns:

link(f)

linkInv

public double linkInv(double f)

Canonical link inverse

Parameters:

f - value in link space, to be transformed back to original space

Returns:

linkInv(f)

linkInvString

public java.lang.String linkInvString(java.lang.String f)

String version of link inverse (for POJO scoring code generation)

Parameters:

f - value to be transformed by link inverse

Returns:

String that turns into compilable expression of linkInv(f)

initFNum

public double initFNum(double w,
              double o,
              double y)

Contribution to numerator for initial value computation

Parameters:

w - weight

o - offset

y - response

Returns:

weighted contribution to numerator

initFDenom

public double initFDenom(double w,
                double o)

Contribution to denominator for initial value computation

Parameters:

w - weight

o - offset

Returns:

weighted contribution to denominator

gammaNum

public double gammaNum(double w,
              double y,
              double z,
              double f)

Contribution to numerator for GBM's leaf node prediction

Parameters:

w - weight

y - response

z - residual

f - predicted value (including offset)

Returns:

weighted contribution to numerator

gammaDenom

public double gammaDenom(double w,
                double y,
                double z,
                double f)

Contribution to denominator for GBM's leaf node prediction

Parameters:

w - weight

y - response

z - residual

f - predicted value (including offset)

Returns:

weighted contribution to denominator