water.bindings.pojos

Class AggregatorParametersV99

java.lang.Object

water.bindings.pojos.SchemaV3

water.bindings.pojos.ModelParametersSchemaV3

water.bindings.pojos.AggregatorParametersV99

public class AggregatorParametersV99
extends ModelParametersSchemaV3

Field Summary

Fields

Modifier and Type	Field and Description
int	k Rank of matrix approximation
int	maxIterations Maximum number of iterations for PCA
int	numIterationWithoutNewExemplar The number of iterations to run before aggregator exits if the number of exemplars collected didn't change
PCAMethod	pcaMethod Method for computing PCA (Caution: GLRM is currently experimental and unstable)
double	relTolNumExemplars Relative tolerance for number of exemplars (e.g, 0.5 is +/- 50 percents)
boolean	saveMappingFrame Whether to export the mapping of the aggregated frame
long	seed RNG seed for initialization
int	targetNumExemplars Targeted number of exemplars
DataInfoTransformType	transform Transformation of training data
boolean	useAllFactorLevels Whether first factor level is included in each categorical expansion

Fields inherited from class water.bindings.pojos.ModelParametersSchemaV3

categoricalEncoding, checkpoint, customMetricFunc, distribution, exportCheckpointsDir, foldAssignment, foldColumn, huberAlpha, ignoreConstCols, ignoredColumns, keepCrossValidationFoldAssignment, keepCrossValidationModels, keepCrossValidationPredictions, maxCategoricalLevels, maxRuntimeSecs, modelId, nfolds, offsetColumn, parallelizeCrossValidation, quantileAlpha, responseColumn, scoreEachIteration, stoppingMetric, stoppingRounds, stoppingTolerance, trainingFrame, tweediePower, validationFrame, weightsColumn

Constructor Summary

Constructors

Constructor and Description
AggregatorParametersV99() Public constructor

Method Summary

Modifier and Type	Method and Description
java.lang.String	toString() Return the contents of this object as a JSON String.

Methods inherited from class java.lang.Object

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

Field Detail

transform

public DataInfoTransformType transform

Transformation of training data

pcaMethod

@SerializedName(value="pca_method")
public PCAMethod pcaMethod

Method for computing PCA (Caution: GLRM is currently experimental and unstable)

k

public int k

Rank of matrix approximation

maxIterations

@SerializedName(value="max_iterations")
public int maxIterations

Maximum number of iterations for PCA

targetNumExemplars

@SerializedName(value="target_num_exemplars")
public int targetNumExemplars

Targeted number of exemplars

relTolNumExemplars

@SerializedName(value="rel_tol_num_exemplars")
public double relTolNumExemplars

Relative tolerance for number of exemplars (e.g, 0.5 is +/- 50 percents)

seed

public long seed

RNG seed for initialization

useAllFactorLevels

@SerializedName(value="use_all_factor_levels")
public boolean useAllFactorLevels

Whether first factor level is included in each categorical expansion

saveMappingFrame

@SerializedName(value="save_mapping_frame")
public boolean saveMappingFrame

Whether to export the mapping of the aggregated frame

numIterationWithoutNewExemplar

@SerializedName(value="num_iteration_without_new_exemplar")
public int numIterationWithoutNewExemplar

The number of iterations to run before aggregator exits if the number of exemplars collected didn't change

Constructor Detail

AggregatorParametersV99

public AggregatorParametersV99()

Public constructor

Method Detail

toString

public java.lang.String toString()

Return the contents of this object as a JSON String.

Overrides:

toString in class ModelParametersSchemaV3