hex.genmodel.algos.isoforextended

Class ExtendedIsolationForestMojoModel

java.lang.Object

hex.genmodel.GenModel

hex.genmodel.MojoModel

hex.genmodel.algos.isoforextended.ExtendedIsolationForestMojoModel

All Implemented Interfaces:

IGenModel, java.io.Serializable, IGeneratedModel

public final class ExtendedIsolationForestMojoModel
extends MojoModel

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	LEAF
static int	NODE

Fields inherited from class hex.genmodel.MojoModel

_algoName, _balanceClasses, _category, _defaultThreshold, _h2oVersion, _modelAttributes, _modelClassDistrib, _modelDescriptor, _mojo_version, _nclasses, _nfeatures, _priorClassDistrib, _reproducibilityInformation, _supervised, _uuid

Fields inherited from class hex.genmodel.GenModel

_domains, _names, _offsetColumn, _responseColumn, _treatmentColumn

Constructor Summary

Constructors

Constructor and Description
ExtendedIsolationForestMojoModel(java.lang.String[] columns, java.lang.String[][] domains, java.lang.String responseColumn)

Method Summary

Modifier and Type	Method and Description
static double	anomalyScore(double pathLength, long sample_size) Anomaly score computation comes from Equation 1 in paper
static double	averagePathLengthOfUnsuccessfulSearch(long n) Gives the average path length of unsuccessful search in BST.
java.lang.String[]	getOutputNames()
int	getPredsSize() Returns the expected size of preds array which is passed to `predict(double[], double[])` function.
static int	leftChildIndex(int i)
void	postInit()
static int	rightChildIndex(int i)
double[]	score0(double[] row, double[] preds) Subclasses implement the scoring logic.
double[]	score0(double[] row, double offset, double[] preds)
static double	scoreTree0(byte[] isolationTree, double[] row)

Methods inherited from class hex.genmodel.MojoModel

getModelCategory, getUUID, isSupervised, load, load, load, nclasses, nfeatures

Methods inherited from class hex.genmodel.GenModel

bitSetContains, bitSetIsInRange, calibrateClassProbabilities, convertDouble2Float, correctProbabilities, createAuxKey, features, GBM_rescale, getCategoricalEncoding, getColIdx, getDomainValues, getDomainValues, getDomainValues, getHeader, getModelCategories, getNames, getNumClasses, getNumCols, getNumResponseClasses, getOffsetName, getOrigDomainValues, getOrigNames, getOrigNumCols, getOrigProjectionArray, getOutputDomains, getPrediction, getPredictionBinomial, getPredictionMultinomial, getPredsSize, getResponseIdx, getResponseName, GLM_identityInv, GLM_inverseInv, GLM_logInv, GLM_logitInv, GLM_ologitInv, GLM_tweedieInv, img2pixels, internal_threadSafeInstance, isAutoEncoder, isClassifier, KMeans_closest, KMeans_distance, KMeans_distance, KMeans_distances, Kmeans_preprocessData, Kmeans_preprocessData, KMeans_simplex, log_rescale, mapEnum, nCatFeatures, requiresOffset, setCats, setCats, setInput, setInput

Methods inherited from class java.lang.Object

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

Field Detail

NODE

public static final int NODE

See Also:

Constant Field Values

LEAF

public static final int LEAF

See Also:

Constant Field Values

Constructor Detail

ExtendedIsolationForestMojoModel

public ExtendedIsolationForestMojoModel(java.lang.String[] columns,
                                        java.lang.String[][] domains,
                                        java.lang.String responseColumn)

Method Detail

postInit

public void postInit()

score0

public double[] score0(double[] row,
                       double[] preds)

Description copied from class: GenModel

Subclasses implement the scoring logic. The data is pre-loaded into a re-used temp array, in the order the model expects. The predictions are loaded into the re-used temp array, which is also returned. This call exactly matches the hex.Model.score0, but uses the light-weight GenModel class.

Specified by:

score0 in class GenModel

score0

public double[] score0(double[] row,
                       double offset,
                       double[] preds)

Overrides:

score0 in class GenModel

getPredsSize

public int getPredsSize()

Description copied from class: GenModel

Returns the expected size of preds array which is passed to `predict(double[], double[])` function.

Specified by:

getPredsSize in interface IGeneratedModel

Overrides:

getPredsSize in class GenModel

Returns:

expected size of preds array

getOutputNames

public java.lang.String[] getOutputNames()

Overrides:

getOutputNames in class GenModel

scoreTree0

public static double scoreTree0(byte[] isolationTree,
                                double[] row)

leftChildIndex

public static int leftChildIndex(int i)

rightChildIndex

public static int rightChildIndex(int i)

anomalyScore

public static double anomalyScore(double pathLength,
                                  long sample_size)

Anomaly score computation comes from Equation 1 in paper

Parameters:

pathLength - path from root to leaf

Returns:

anomaly score in range [0, 1]

averagePathLengthOfUnsuccessfulSearch

public static double averagePathLengthOfUnsuccessfulSearch(long n)

Gives the average path length of unsuccessful search in BST. Comes from Algorithm 3 (pathLength) and Equation 2 in paper

Parameters:

n - number of elements