hex.glm

Class GLMModel

java.lang.Object

water.Iced

water.Lockable<Model>

water.Model

hex.glm.GLMModel

All Implemented Interfaces:

java.lang.Cloneable, java.lang.Comparable<GLMModel>, Freezable

public class GLMModel
extends Model
implements java.lang.Comparable<GLMModel>

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GLMModel.GLMValidationTask<T extends GLMModel.GLMValidationTask<T>>
static class	GLMModel.GLMXValidationTask

Nested classes/interfaces inherited from class water.Model

Model.ModelCategory

Field Summary

Fields

Modifier and Type	Field and Description
java.lang.String[]	coefficients_names
static DocGen.FieldDoc[]	DOC_FIELDS

Fields inherited from class water.Model

_dataKey, _domains, _modelClassDist, _names, _priorClassDist, training_duration_in_ms, training_start_time

Fields inherited from class water.Lockable

_key, _lockers

Constructor Summary

Constructors

Constructor and Description
GLMModel(GLM2 job, Key selfKey, FrameTask.DataInfo dinfo, GLMParams glm, double beta_eps, double alpha, double lambda_max, double[] lambda, double ymu, double prior)

Method Summary

Methods

Modifier and Type	Method and Description
double	aic()
double	auc()
double[]	beta()
GLMModel	clone()
java.util.HashMap<java.lang.String,java.lang.Double>	coefficients() get beta coefficients in a map indexed by name
int	compareTo(GLMModel m)
double	devExplained()
GLM2	get_params()
GLMParams	getParams()
int	iteration()
Request2	job()
double	lambda()
double	lambdaMax()
double	lambdaMin()
int	ncoefs()
double[]	norm_beta(int lambdaIdx)
int	rank()
int	rank(int lambdaIdx)
protected float[]	score0(double[] data, float[] preds) Subclasses implement the scoring logic.
boolean	setAndTestValidation(int lambdaIdx, GLMValidation val)
void	setLambdaIdx(int l)
void	setLambdaSubmodel(int lambdaIdx, double[] beta, double[] norm_beta, int iteration, boolean sparseCoef)
java.lang.String	toString()
GLMValidation	validation()

Methods inherited from class water.Model

adapt, calcError, classNames, cm, delete_impl, errStr, getDomainMapping, getDomainMapping, getModelCategory, getUniqueId, isClassifier, missingColumnsType, mse, nclasses, nfeatures, responseName, score, score, score, score, score, score, score0, setModelClassDistribution, start_training, start_training, stop_training, testJavaScoring, toJava, toJava, toJavaDefaultMaxIters, toJavaInit, toJavaInit, toJavaPredictBody, toJavaSuper, varimp

Methods inherited from class water.Lockable

delete_and_lock, delete, delete, delete, delete, is_unlocked, is_wlocked, read_lock, read_lock, unlock_all, unlock, update, write_lock

Methods inherited from class water.Iced

frozenType, init, newInstance, read, toDocField, write, writeJSON, writeJSONFields

Methods inherited from class java.lang.Object

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

Field Detail

DOC_FIELDS

public static DocGen.FieldDoc[] DOC_FIELDS

coefficients_names

@Request.API(help="column names including expanded categorical values")
public java.lang.String[] coefficients_names

Constructor Detail

GLMModel

public GLMModel(GLM2 job,
        Key selfKey,
        FrameTask.DataInfo dinfo,
        GLMParams glm,
        double beta_eps,
        double alpha,
        double lambda_max,
        double[] lambda,
        double ymu,
        double prior)

Method Detail

get_params

public final GLM2 get_params()

Overrides:

get_params in class Model

job

public final Request2 job()

Overrides:

job in class Model

auc

public double auc()

aic

public double aic()

devExplained

public double devExplained()

clone

public GLMModel clone()

Overrides:

clone in class Iced

compareTo

public int compareTo(GLMModel m)

Specified by:

compareTo in interface java.lang.Comparable<GLMModel>

setLambdaSubmodel

public void setLambdaSubmodel(int lambdaIdx,
                     double[] beta,
                     double[] norm_beta,
                     int iteration,
                     boolean sparseCoef)

lambda

public double lambda()

lambdaMax

public double lambdaMax()

lambdaMin

public double lambdaMin()

validation

public GLMValidation validation()

iteration

public int iteration()

beta

public double[] beta()

norm_beta

public double[] norm_beta(int lambdaIdx)

score0

protected float[] score0(double[] data,
             float[] preds)

Description copied from class: Model

Subclasses implement the scoring logic. The data is pre-loaded into a re-used temp array, in the order the model expects. The predictions are loaded into the re-used temp array, which is also returned.

Specified by:

score0 in class Model

ncoefs

public final int ncoefs()

getParams

public GLMParams getParams()

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

rank

public int rank()

rank

public int rank(int lambdaIdx)

setAndTestValidation

public boolean setAndTestValidation(int lambdaIdx,
                           GLMValidation val)

setLambdaIdx

public void setLambdaIdx(int l)

coefficients

public java.util.HashMap<java.lang.String,java.lang.Double> coefficients()

get beta coefficients in a map indexed by name

Returns: