hex.schemas

Class GLRMV99.GLRMParametersV99

java.lang.Object

water.Iced

water.api.Schema<P,S>

water.api.ModelParametersSchema<GLRMModel.GLRMParameters,GLRMV99.GLRMParametersV99>

hex.schemas.GLRMV99.GLRMParametersV99

All Implemented Interfaces:

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

Enclosing class:

GLRMV99

public static final class GLRMV99.GLRMParametersV99
extends water.api.ModelParametersSchema<GLRMModel.GLRMParameters,GLRMV99.GLRMParametersV99>

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class water.api.Schema

water.api.Schema.Meta

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String[]	fields
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.api.KeyV3.FrameKeyV3	user_points

Fields inherited from class water.api.ModelParametersSchema

checkpoint, fold_assignment, fold_column, ignore_const_cols, ignored_columns, keep_cross_validation_predictions, model_id, nfolds, offset_column, response_column, score_each_iteration, training_frame, validation_frame, weights_column

Constructor Summary

Constructors

Constructor and Description
GLRMV99.GLRMParametersV99()

Method Summary

Methods inherited from class water.api.ModelParametersSchema

append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSON

Methods inherited from class water.api.Schema

createAndFillImpl, createImpl, fillFromParms, fillFromParms, get__meta, getExperimentalVersion, getHighestSupportedVersion, getImplClass, getImplClass, getLatestVersion, getSchemaVersion, markdown, markdown, markdown, newInstance, newInstance, registerAllSchemasIfNecessary, schema, schema, schemaClass, schemas, setField

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

fields

public static java.lang.String[] fields

transform

@API(help="Transformation of training data",
     values={"NONE","STANDARDIZE","NORMALIZE","DEMEAN","DESCALE"})
public DataInfo.TransformType transform

k

@API(help="Rank of matrix approximation",
     required=true,
     gridable=true)
public int k

loss

@API(help="Numeric loss function",
     values={"Quadratic","L1","Huber","Poisson","Hinge","Logistic","Periodic"})
public GLRMModel.GLRMParameters.Loss loss

multi_loss

@API(help="Enum loss function",
     values={"Categorical","Ordinal"})
public GLRMModel.GLRMParameters.Loss multi_loss

loss_by_col

@API(help="Loss function by column (override)",
     values={"Quadratic","L1","Huber","Poisson","Hinge","Logistic","Periodic","Categorical","Ordinal"})
public GLRMModel.GLRMParameters.Loss[] loss_by_col

loss_by_col_idx

@API(help="Loss function by column index (override)")
public int[] loss_by_col_idx

period

@API(help="Length of period (only used with periodic loss function)",
     gridable=true)
public int period

regularization_x

@API(help="Regularization function for X matrix",
     values={"None","Quadratic","L2","L1","NonNegative","OneSparse","UnitOneSparse","Simplex"})
public GLRMModel.GLRMParameters.Regularizer regularization_x

regularization_y

@API(help="Regularization function for Y matrix",
     values={"None","Quadratic","L2","L1","NonNegative","OneSparse","UnitOneSparse","Simplex"})
public GLRMModel.GLRMParameters.Regularizer regularization_y

gamma_x

@API(help="Regularization weight on X matrix",
     gridable=true)
public double gamma_x

gamma_y

@API(help="Regularization weight on Y matrix",
     gridable=true)
public double gamma_y

max_iterations

@API(help="Maximum number of iterations")
public int max_iterations

init_step_size

@API(help="Initial step size",
     gridable=true)
public double init_step_size

min_step_size

@API(help="Minimum step size",
     gridable=true)
public double min_step_size

seed

@API(help="RNG seed for initialization")
public long seed

init

@API(help="Initialization mode",
     values={"Random","SVD","PlusPlus","User"})
public GLRM.Initialization init

user_points

@API(help="User-specified initial Y",
     required=false)
public water.api.KeyV3.FrameKeyV3 user_points

loading_name

@API(help="Frame key to save resulting X")
public java.lang.String loading_name

recover_svd

@API(help="Recover singular values and eigenvectors of XY")
public boolean recover_svd

Constructor Detail

GLRMV99.GLRMParametersV99

public GLRMV99.GLRMParametersV99()