public final class ExtendedIsolationForestMojoModel extends MojoModel
Modifier and Type | Field and Description |
---|---|
static int |
LEAF |
static int |
NODE |
_algoName, _balanceClasses, _category, _defaultThreshold, _h2oVersion, _modelAttributes, _modelClassDistrib, _modelDescriptor, _mojo_version, _nclasses, _nfeatures, _priorClassDistrib, _reproducibilityInformation, _supervised, _uuid
_domains, _foldColumn, _names, _offsetColumn, _responseColumn, _treatmentColumn
Constructor and Description |
---|
ExtendedIsolationForestMojoModel(java.lang.String[] columns,
java.lang.String[][] domains,
java.lang.String responseColumn) |
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) |
getModelCategory, getUUID, isSupervised, load, load, load, nclasses, nfeatures
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
public static final int NODE
public static final int LEAF
public ExtendedIsolationForestMojoModel(java.lang.String[] columns, java.lang.String[][] domains, java.lang.String responseColumn)
public void postInit()
public double[] score0(double[] row, double[] preds)
GenModel
public double[] score0(double[] row, double offset, double[] preds)
public int getPredsSize()
GenModel
getPredsSize
in interface IGeneratedModel
getPredsSize
in class GenModel
public java.lang.String[] getOutputNames()
getOutputNames
in class GenModel
public static double scoreTree0(byte[] isolationTree, double[] row)
public static int leftChildIndex(int i)
public static int rightChildIndex(int i)
public static double anomalyScore(double pathLength, long sample_size)
pathLength
- path from root to leafpublic static double averagePathLengthOfUnsuccessfulSearch(long n)
n
- number of elements