hex.tree.isoforextended

Class ExtendedIsolationForestModel.ExtendedIsolationForestParameters

java.lang.Object

water.Iced<hex.Model.Parameters>

hex.Model.Parameters

hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

All Implemented Interfaces:

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

Enclosing class:

ExtendedIsolationForestModel

public static class ExtendedIsolationForestModel.ExtendedIsolationForestParameters
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
boolean	_disable_training_metrics Disable calculating training metrics (expensive on large datasets).
int	_extension_level Maximum is N - 1 (N = numCols).
int	_initial_score_interval For _initial_score_interval milliseconds - score each iteration of the algorithm.
int	_ntrees Number of trees in the forest
int	_sample_size Number of randomly selected rows from original data before each tree build.
int	_score_interval After each _score_interval milliseconds - run scoring But limit the scoring time consumption to 10% of whole training time.
int	_score_tree_interval Score every so many trees (no matter what)

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
ExtendedIsolationForestParameters()

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

_ntrees

public int _ntrees

Number of trees in the forest

_extension_level

public int _extension_level

Maximum is N - 1 (N = numCols). Minimum is 0. EIF with extension_level = 0 behaves like Isolation Forest.

_sample_size

public int _sample_size

Number of randomly selected rows from original data before each tree build.

_score_tree_interval

public int _score_tree_interval

Score every so many trees (no matter what)

_disable_training_metrics

public boolean _disable_training_metrics

Disable calculating training metrics (expensive on large datasets).

_initial_score_interval

public int _initial_score_interval

For _initial_score_interval milliseconds - score each iteration of the algorithm.

_score_interval

public int _score_interval

After each _score_interval milliseconds - run scoring But limit the scoring time consumption to 10% of whole training time.

Constructor Detail

ExtendedIsolationForestParameters

public ExtendedIsolationForestParameters()

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