water.automl.api.schemas3

Class AutoMLBuildSpecV99.AutoMLBuildControlV99

java.lang.Object

water.Iced

water.api.Schema<I,S>

water.api.schemas3.SchemaV3<AutoMLBuildSpec.AutoMLBuildControl,AutoMLBuildSpecV99.AutoMLBuildControlV99>

water.automl.api.schemas3.AutoMLBuildSpecV99.AutoMLBuildControlV99

All Implemented Interfaces:

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

Enclosing class:

AutoMLBuildSpecV99

public static final class AutoMLBuildSpecV99.AutoMLBuildControlV99
extends water.api.schemas3.SchemaV3<AutoMLBuildSpec.AutoMLBuildControl,AutoMLBuildSpecV99.AutoMLBuildControlV99>

The specification of overall build parameters for the AutoML process. TODO: this should have all the standard early-stopping functionality like Grid does.

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
boolean	balance_classes
float[]	class_sampling_factors
java.lang.String	custom_distribution_func
java.lang.String	custom_metric_func
hex.genmodel.utils.DistributionFamily	distribution
java.lang.String	export_checkpoints_dir
double	huber_alpha
boolean	keep_cross_validation_fold_assignment
boolean	keep_cross_validation_models
boolean	keep_cross_validation_predictions
float	max_after_balance_size
int	nfolds
java.lang.String	project_name
double	quantile_alpha
AutoMLBuildSpecV99.AutoMLStoppingCriteriaV99	stopping_criteria
double	tweedie_power

Fields inherited from class water.api.schemas3.SchemaV3

__meta

Constructor Summary

Constructors

Constructor and Description
AutoMLBuildControlV99()

Method Summary

Methods inherited from class water.api.schemas3.SchemaV3

writeJSON

Methods inherited from class water.api.Schema

createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromAny, fillFromBody, fillFromImpl, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillFromParms, fillImpl, 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

project_name

@API(help="Optional project name used to group models from multiple AutoML runs into a single Leaderboard; derived from the training data name if not specified.",
     direction=INOUT)
public java.lang.String project_name

stopping_criteria

@API(help="Model performance based stopping criteria for the AutoML run.")
public AutoMLBuildSpecV99.AutoMLStoppingCriteriaV99 stopping_criteria

nfolds

@API(help="Number of folds for k-fold cross-validation (defaults to -1 (AUTO), otherwise it must be >=2 or use 0 to disable). Disabling prevents Stacked Ensembles from being built.",
     level=secondary)
public int nfolds

balance_classes

@API(help="Balance training data class counts via over/under-sampling (for imbalanced data).",
     level=secondary)
public boolean balance_classes

class_sampling_factors

@API(help="Desired over/under-sampling ratios per class (in lexicographic order). If not specified, sampling factors will be automatically computed to obtain class balance during training. Requires balance_classes.",
     level=expert)
public float[] class_sampling_factors

max_after_balance_size

@API(help="Maximum relative size of the training data after balancing class counts (defaults to 5.0 and can be less than 1.0). Requires balance_classes.",
     level=expert)
public float max_after_balance_size

keep_cross_validation_predictions

@API(help="Whether to keep the predictions of the cross-validation predictions. This needs to be set to TRUE if running the same AutoML object for repeated runs because CV predictions are required to build additional Stacked Ensemble models in AutoML.",
     level=expert)
public boolean keep_cross_validation_predictions

keep_cross_validation_models

@API(help="Whether to keep the cross-validated models. Keeping cross-validation models may consume significantly more memory in the H2O cluster.",
     level=expert)
public boolean keep_cross_validation_models

keep_cross_validation_fold_assignment

@API(help="Whether to keep cross-validation assignments.",
     level=expert)
public boolean keep_cross_validation_fold_assignment

export_checkpoints_dir

@API(help="Path to a directory where every generated model will be stored.",
     level=expert)
public java.lang.String export_checkpoints_dir

distribution

@API(help="Distribution function used by algorithms that support it; other algorithms use their defaults.",
     direction=INOUT,
     values={"AUTO","bernoulli","multinomial","gaussian","poisson","gamma","tweedie","laplace","quantile","huber","custom"})
public hex.genmodel.utils.DistributionFamily distribution

tweedie_power

@API(direction=INPUT,
     help="Tweedie power for Tweedie regression, must be between 1 and 2.")
public double tweedie_power

quantile_alpha

@API(direction=INPUT,
     help="Desired quantile for Quantile regression, must be between 0 and 1.")
public double quantile_alpha

huber_alpha

@API(direction=INPUT,
     help="Desired quantile for Huber/M-regression (threshold between quadratic and linear loss, must be between 0 and 1).")
public double huber_alpha

custom_metric_func

@API(help="Reference to custom evaluation function, format: `language:keyName=funcName`",
     level=secondary,
     direction=INOUT,
     gridable=false)
public java.lang.String custom_metric_func

custom_distribution_func

@API(help="Reference to custom distribution, format: `language:keyName=funcName`",
     direction=INOUT)
public java.lang.String custom_distribution_func

Constructor Detail

AutoMLBuildControlV99

public AutoMLBuildControlV99()