hex.schemas

Class GLRMV3.GLRMParametersV3

java.lang.Object

water.Iced

water.api.Schema<I,S>

water.api.schemas3.SchemaV3<P,S>

water.api.schemas3.ModelParametersSchemaV3<GLRMModel.GLRMParameters,GLRMV3.GLRMParametersV3>

hex.schemas.GLRMV3.GLRMParametersV3

All Implemented Interfaces:

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

Enclosing class:

GLRMV3

public static final class GLRMV3.GLRMParametersV3
extends water.api.schemas3.ModelParametersSchemaV3<GLRMModel.GLRMParameters,GLRMV3.GLRMParametersV3>

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class water.api.schemas3.SchemaV3

water.api.schemas3.SchemaV3.Meta

Field Summary

Fields

Modifier and Type	Field and Description
boolean	expand_user_y
static java.lang.String[]	fields
double	gamma_x
double	gamma_y
boolean	impute_original
hex.genmodel.algos.glrm.GlrmInitialization	init
double	init_step_size
int	k
java.lang.String	loading_name
hex.genmodel.algos.glrm.GlrmLoss	loss
hex.genmodel.algos.glrm.GlrmLoss[]	loss_by_col
int[]	loss_by_col_idx
int	max_iterations
int	max_updates
double	min_step_size
hex.genmodel.algos.glrm.GlrmLoss	multi_loss
int	period
boolean	recover_svd
hex.genmodel.algos.glrm.GlrmRegularizer	regularization_x
hex.genmodel.algos.glrm.GlrmRegularizer	regularization_y
long	seed
SVDModel.SVDParameters.Method	svd_method
DataInfo.TransformType	transform
water.api.schemas3.KeyV3.FrameKeyV3	user_x
water.api.schemas3.KeyV3.FrameKeyV3	user_y

Fields inherited from class water.api.schemas3.ModelParametersSchemaV3

categorical_encoding, checkpoint, distribution, fold_assignment, fold_column, huber_alpha, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_predictions, max_categorical_levels, max_runtime_secs, model_id, nfolds, offset_column, parallelize_cross_validation, quantile_alpha, response_column, score_each_iteration, stopping_metric, stopping_rounds, stopping_tolerance, training_frame, tweedie_power, validation_frame, weights_column

Fields inherited from class water.api.schemas3.SchemaV3

__meta

Constructor Summary

Constructors

Constructor and Description
GLRMV3.GLRMParametersV3()

Method Summary

Methods inherited from class water.api.schemas3.ModelParametersSchemaV3

append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSON

Methods inherited from class water.api.schemas3.SchemaV3

writeJSON

Methods inherited from class water.api.Schema

createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCall

Methods inherited from class water.Iced

asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonString, write, writeExternal

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"},
     gridable=true)
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","Absolute","Huber","Poisson","Hinge","Logistic","Periodic"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmLoss loss

multi_loss

@API(help="Categorical loss function",
     values={"Categorical","Ordinal"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmLoss multi_loss

loss_by_col

@API(help="Loss function by column (override)",
     values={"Quadratic","Absolute","Huber","Poisson","Hinge","Logistic","Periodic","Categorical","Ordinal"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmLoss[] 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"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmRegularizer regularization_x

regularization_y

@API(help="Regularization function for Y matrix",
     values={"None","Quadratic","L2","L1","NonNegative","OneSparse","UnitOneSparse","Simplex"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmRegularizer 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",
     gridable=true)
public int max_iterations

max_updates

@API(help="Maximum number of updates, defaults to 2*max_iterations",
     gridable=true)
public int max_updates

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",
     gridable=true)
public long seed

init

@API(help="Initialization mode",
     values={"Random","SVD","PlusPlus","User"},
     gridable=true)
public hex.genmodel.algos.glrm.GlrmInitialization init

svd_method

@API(help="Method for computing SVD during initialization (Caution: Randomized is currently experimental and unstable)",
     values={"GramSVD","Power","Randomized"},
     gridable=true)
public SVDModel.SVDParameters.Method svd_method

user_y

@API(help="User-specified initial Y")
public water.api.schemas3.KeyV3.FrameKeyV3 user_y

user_x

@API(help="User-specified initial X")
public water.api.schemas3.KeyV3.FrameKeyV3 user_x

loading_name

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

expand_user_y

@API(help="Expand categorical columns in user-specified initial Y")
public boolean expand_user_y

impute_original

@API(help="Reconstruct original training data by reversing transform")
public boolean impute_original

recover_svd

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

Constructor Detail

GLRMV3.GLRMParametersV3

public GLRMV3.GLRMParametersV3()