hex.glrm

Class GLRMModel.GLRMParameters

java.lang.Object

water.Iced

hex.Model.Parameters

hex.glrm.GLRMModel.GLRMParameters

All Implemented Interfaces:

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

Enclosing class:

GLRMModel

public static class GLRMModel.GLRMParameters
extends hex.Model.Parameters

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GLRMModel.GLRMParameters.Loss
static class	GLRMModel.GLRMParameters.Regularizer

Nested classes/interfaces inherited from class hex.Model.Parameters

hex.Model.Parameters.FoldAssignmentScheme

Field Summary

Fields

Modifier and Type	Field and Description
double	_gamma_x
double	_gamma_y
GLRM.Initialization	_init
double	_init_step_size
int	_k
java.lang.String	_loading_name
GLRMModel.GLRMParameters.Loss	_loss
GLRMModel.GLRMParameters.Loss[]	_loss_by_col
int[]	_loss_by_col_idx
int	_max_iterations
double	_min_step_size
GLRMModel.GLRMParameters.Loss	_multi_loss
int	_period
boolean	_recover_svd
GLRMModel.GLRMParameters.Regularizer	_regularization_x
GLRMModel.GLRMParameters.Regularizer	_regularization_y
long	_seed
DataInfo.TransformType	_transform
water.Key<water.fvec.Frame>	_user_points
boolean	_verbose

Fields inherited from class hex.Model.Parameters

_balance_classes, _checkpoint, _class_sampling_factors, _distribution, _fold_assignment, _fold_column, _ignore_const_cols, _ignored_columns, _keep_cross_validation_predictions, _max_after_balance_size, _max_confusion_matrix_size, _max_hit_ratio_k, _model_id, _nfolds, _offset_column, _response_column, _score_each_iteration, _train, _tweedie_power, _valid, _weights_column, MAX_SUPPORTED_LEVELS

Constructor Summary

Constructors

Constructor and Description
GLRMModel.GLRMParameters()

Method Summary

Methods

Modifier and Type	Method and Description
boolean	hasClosedForm()
boolean	hasClosedForm(long na_cnt)
double	impute(double u)
static double	impute(double u, GLRMModel.GLRMParameters.Loss loss)
double	lgrad(double u, double a)
double	lgrad(double u, double a, GLRMModel.GLRMParameters.Loss loss)
double	loss(double u, double a)
double	loss(double u, double a, GLRMModel.GLRMParameters.Loss loss)
int	mimpute(double[] u)
static int	mimpute(double[] u, GLRMModel.GLRMParameters.Loss multi_loss)
double[]	mlgrad(double[] u, int a)
static double[]	mlgrad(double[] u, int a, GLRMModel.GLRMParameters.Loss multi_loss)
double	mloss(double[] u, int a)
static double	mloss(double[] u, int a, GLRMModel.GLRMParameters.Loss multi_loss)
double[]	project_x(double[] u, java.util.Random rand)
double[]	project_y(double[] u, java.util.Random rand)
double[]	project(double[] u, GLRMModel.GLRMParameters.Regularizer regularization, java.util.Random rand)
double	regularize_x(double[] u)
double	regularize_x(double[][] u)
double	regularize_y(double[] u)
double	regularize_y(double[][] u)
double	regularize(double[][] u, GLRMModel.GLRMParameters.Regularizer regularization)
double	regularize(double[] u, GLRMModel.GLRMParameters.Regularizer regularization)
double[]	rproxgrad_x(double[] u, double alpha, java.util.Random rand)
double[]	rproxgrad_y(double[] u, double alpha, java.util.Random rand)

Methods inherited from class hex.Model.Parameters

checksum_impl, checksum, defaultDropConsCols, defaultDropNA20Cols, hasCheckpoint, missingColumnsType, read_lock_frames, read_unlock_frames, train, valid

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

_transform

public DataInfo.TransformType _transform

_k

public int _k

_init

public GLRM.Initialization _init

_user_points

public water.Key<water.fvec.Frame> _user_points

_loss

public GLRMModel.GLRMParameters.Loss _loss

_multi_loss

public GLRMModel.GLRMParameters.Loss _multi_loss

_period

public int _period

_loss_by_col

public GLRMModel.GLRMParameters.Loss[] _loss_by_col

_loss_by_col_idx

public int[] _loss_by_col_idx

_regularization_x

public GLRMModel.GLRMParameters.Regularizer _regularization_x

_regularization_y

public GLRMModel.GLRMParameters.Regularizer _regularization_y

_gamma_x

public double _gamma_x

_gamma_y

public double _gamma_y

_max_iterations

public int _max_iterations

_init_step_size

public double _init_step_size

_min_step_size

public double _min_step_size

_seed

public long _seed

_loading_name

public java.lang.String _loading_name

_recover_svd

public boolean _recover_svd

_verbose

public boolean _verbose

Constructor Detail

GLRMModel.GLRMParameters

public GLRMModel.GLRMParameters()

Method Detail

hasClosedForm

public final boolean hasClosedForm()

hasClosedForm

public final boolean hasClosedForm(long na_cnt)

loss

public final double loss(double u,
          double a)

loss

public final double loss(double u,
          double a,
          GLRMModel.GLRMParameters.Loss loss)

lgrad

public final double lgrad(double u,
           double a)

lgrad

public final double lgrad(double u,
           double a,
           GLRMModel.GLRMParameters.Loss loss)

mloss

public final double mloss(double[] u,
           int a)

mloss

public static double mloss(double[] u,
           int a,
           GLRMModel.GLRMParameters.Loss multi_loss)

mlgrad

public final double[] mlgrad(double[] u,
              int a)

mlgrad

public static double[] mlgrad(double[] u,
              int a,
              GLRMModel.GLRMParameters.Loss multi_loss)

regularize_x

public final double regularize_x(double[] u)

regularize_y

public final double regularize_y(double[] u)

regularize

public final double regularize(double[] u,
                GLRMModel.GLRMParameters.Regularizer regularization)

regularize_x

public final double regularize_x(double[][] u)

regularize_y

public final double regularize_y(double[][] u)

regularize

public final double regularize(double[][] u,
                GLRMModel.GLRMParameters.Regularizer regularization)

rproxgrad_x

public final double[] rproxgrad_x(double[] u,
                   double alpha,
                   java.util.Random rand)

rproxgrad_y

public final double[] rproxgrad_y(double[] u,
                   double alpha,
                   java.util.Random rand)

project_x

public final double[] project_x(double[] u,
                 java.util.Random rand)

project_y

public final double[] project_y(double[] u,
                 java.util.Random rand)

project

public final double[] project(double[] u,
               GLRMModel.GLRMParameters.Regularizer regularization,
               java.util.Random rand)

impute

public final double impute(double u)

impute

public static double impute(double u,
            GLRMModel.GLRMParameters.Loss loss)

mimpute

public final int mimpute(double[] u)

mimpute

public static int mimpute(double[] u,
          GLRMModel.GLRMParameters.Loss multi_loss)