hex.schemas

Class AggregatorV99.AggregatorParametersV99

java.lang.Object

water.Iced

water.api.Schema<I,S>

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

water.api.schemas3.ModelParametersSchemaV3<AggregatorModel.AggregatorParameters,AggregatorV99.AggregatorParametersV99>

hex.schemas.AggregatorV99.AggregatorParametersV99

All Implemented Interfaces:

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

Enclosing class:

AggregatorV99

public static final class AggregatorV99.AggregatorParametersV99
extends water.api.schemas3.ModelParametersSchemaV3<AggregatorModel.AggregatorParameters,AggregatorV99.AggregatorParametersV99>

See Also:

Serialized Form

Nested Class Summary

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

water.api.schemas3.SchemaV3.Meta

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

water.api.Schema.AutoParseable

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String[]	fields
int	k
int	max_iterations
int	num_iteration_without_new_exemplar
PCAModel.PCAParameters.Method	pca_method
double	rel_tol_num_exemplars
boolean	save_mapping_frame
long	seed
int	target_num_exemplars
DataInfo.TransformType	transform
boolean	use_all_factor_levels

Fields inherited from class water.api.schemas3.ModelParametersSchemaV3

auc_type, categorical_encoding, checkpoint, custom_distribution_func, custom_metric_func, distribution, export_checkpoints_dir, fold_assignment, fold_column, gainslift_bins, huber_alpha, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_models, 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
AggregatorParametersV99()

Method Summary

Methods inherited from class water.api.schemas3.ModelParametersSchemaV3

append_field_arrays, extractDeclaredApiParameters, fields, fillFromImpl, fillImpl, getAdditionalParameters, writeParametersJSON

Methods inherited from class water.api.schemas3.SchemaV3

writeJSON

Methods inherited from class water.api.Schema

createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromAny, fillFromBody, fillFromImpl, fillFromImpl, fillFromParms, 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, toJsonBytes, 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,
     level=expert)
public DataInfo.TransformType transform

pca_method

@API(help="Method for computing PCA (Caution: GLRM is currently experimental and unstable)",
     values={"GramSVD","Power","Randomized","GLRM"},
     gridable=true,
     level=expert)
public PCAModel.PCAParameters.Method pca_method

k

@API(help="Rank of matrix approximation",
     direction=INOUT,
     gridable=true,
     level=secondary)
public int k

max_iterations

@API(help="Maximum number of iterations for PCA",
     direction=INOUT,
     gridable=true,
     level=expert)
public int max_iterations

target_num_exemplars

@API(help="Targeted number of exemplars",
     direction=INOUT,
     gridable=true,
     level=secondary)
public int target_num_exemplars

rel_tol_num_exemplars

@API(help="Relative tolerance for number of exemplars (e.g, 0.5 is +/- 50 percents)",
     direction=INOUT,
     gridable=true,
     level=secondary)
public double rel_tol_num_exemplars

seed

@API(help="RNG seed for initialization",
     direction=INOUT,
     level=secondary)
public long seed

use_all_factor_levels

@API(help="Whether first factor level is included in each categorical expansion",
     direction=INOUT,
     level=expert)
public boolean use_all_factor_levels

save_mapping_frame

@API(help="Whether to export the mapping of the aggregated frame",
     direction=INOUT,
     level=expert)
public boolean save_mapping_frame

num_iteration_without_new_exemplar

@API(help="The number of iterations to run before aggregator exits if the number of exemplars collected didn\'t change",
     direction=INOUT,
     level=expert)
public int num_iteration_without_new_exemplar

Constructor Detail

AggregatorParametersV99

public AggregatorParametersV99()