water.bindings.pojos

Class IsolationForestParametersV3

java.lang.Object

water.bindings.pojos.SchemaV3

water.bindings.pojos.ModelParametersSchemaV3

water.bindings.pojos.SharedTreeParametersV3

water.bindings.pojos.IsolationForestParametersV3

public class IsolationForestParametersV3
extends SharedTreeParametersV3

Field Summary

Fields

Modifier and Type	Field and Description
int	mtries Number of variables randomly sampled as candidates at each split.
double	sampleRate Rate of randomly sampled observations used to train each Isolation Forest tree.
long	sampleSize Number of randomly sampled observations used to train each Isolation Forest tree.

Fields inherited from class water.bindings.pojos.SharedTreeParametersV3

balanceClasses, buildTreeOneNode, calibrateModel, calibrationFrame, checkConstantResponse, classSamplingFactors, colSampleRateChangePerLevel, colSampleRatePerTree, histogramType, maxAfterBalanceSize, maxConfusionMatrixSize, maxDepth, maxHitRatioK, minRows, minSplitImprovement, nbins, nbinsCats, nbinsTopLevel, ntrees, r2Stopping, sampleRatePerClass, scoreTreeInterval, seed

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
IsolationForestParametersV3() 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

sampleSize

public long sampleSize

Number of randomly sampled observations used to train each Isolation Forest tree. Only one of parameters sample_size and sample_rate should be defined. If sample_rate is defined, sample_size will be ignored.

sampleRate

public double sampleRate

Rate of randomly sampled observations used to train each Isolation Forest tree. Needs to be in range from 0.0 to 1.0. If set to -1, sample_rate is disabled and sample_size will be used instead.

mtries

public int mtries

Number of variables randomly sampled as candidates at each split. If set to -1, defaults (number of predictors)/3.

Constructor Detail

IsolationForestParametersV3

public IsolationForestParametersV3()

Public constructor

Method Detail

toString

public java.lang.String toString()

Return the contents of this object as a JSON String.

Overrides:

toString in class SharedTreeParametersV3