hex.adaboost

Class AdaBoostModel.AdaBoostParameters

java.lang.Object

water.Iced<hex.Model.Parameters>

hex.Model.Parameters

hex.adaboost.AdaBoostModel.AdaBoostParameters

All Implemented Interfaces:

hex.Model.AdaptFrameParameters, java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, water.Freezable<hex.Model.Parameters>

Enclosing class:

AdaBoostModel

public static class AdaBoostModel.AdaBoostParameters
extends hex.Model.Parameters

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class hex.Model.Parameters

hex.Model.Parameters.CategoricalEncodingScheme, hex.Model.Parameters.FoldAssignmentScheme

Field Summary

Fields

Modifier and Type	Field and Description
double	_learn_rate Specify how quickly the training converge.
int	_nlearners Number of weak learners to train.
AdaBoostModel.Algorithm	_weak_learner Choose a weak learner type.
java.lang.String	_weak_learner_params Custom _weak_learner parameters.

Fields inherited from class hex.Model.Parameters

_auc_type, _auto_rebalance, _auuc_nbins, _auuc_type, _balance_classes, _categorical_encoding, _check_constant_response, _checkpoint, _class_sampling_factors, _custom_distribution_func, _custom_metric_func, _cv_fold, _distribution, _export_checkpoints_dir, _fold_assignment, _fold_column, _gainslift_bins, _huber_alpha, _ignore_const_cols, _ignored_columns, _is_cv_model, _keep_cross_validation_fold_assignment, _keep_cross_validation_models, _keep_cross_validation_predictions, _keep_cross_validation_predictions_precision, _main_model_time_budget_factor, _max_after_balance_size, _max_categorical_levels, _max_confusion_matrix_size, _max_runtime_secs, _nfolds, _offset_column, _parallelize_cross_validation, _preprocessors, _pretrained_autoencoder, _quantile_alpha, _response_column, _score_each_iteration, _seed, _stopping_metric, _stopping_rounds, _stopping_tolerance, _train, _treatment_column, _tweedie_power, _valid, _weights_column, MAX_SUPPORTED_LEVELS

Constructor Summary

Constructors

Constructor and Description
AdaBoostParameters()

Method Summary

Modifier and Type	Method and Description
java.lang.String	algoName()
java.lang.String	fullName()
java.lang.String	javaName()
long	progressUnits()

Methods inherited from class hex.Model.Parameters

checksum, checksum, defaultDropConsCols, defaultStoppingTolerance, getCategoricalEncoding, getDependentKeys, getDistributionFamily, getFoldColumn, getMaxCategoricalLevels, getNonPredictors, getOffsetColumn, getOrMakeRealSeed, getResponseColumn, getTreatmentColumn, getUsedColumns, getWeightsColumn, hasCheckpoint, hasCustomMetricFunc, missingColumnsType, read_lock_frames, read_unlock_frames, setDistributionFamily, setTrain, train, valid

Methods inherited from class water.Iced

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

Methods inherited from class java.lang.Object

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

Field Detail

_nlearners

public int _nlearners

Number of weak learners to train. Defaults to 50.

_weak_learner

public AdaBoostModel.Algorithm _weak_learner

Choose a weak learner type. Defaults to DRF.

_learn_rate

public double _learn_rate

Specify how quickly the training converge. Number in (0,1]. Defaults to 0.5.

_weak_learner_params

public java.lang.String _weak_learner_params

Custom _weak_learner parameters.

Constructor Detail

AdaBoostParameters

public AdaBoostParameters()

Method Detail

algoName

public java.lang.String algoName()

Specified by:

algoName in class hex.Model.Parameters

fullName

public java.lang.String fullName()

Specified by:

fullName in class hex.Model.Parameters

javaName

public java.lang.String javaName()

Specified by:

javaName in class hex.Model.Parameters

progressUnits

public long progressUnits()

Specified by:

progressUnits in class hex.Model.Parameters