AnomalyScore: Evaluating isolation trees
In IsolationForest: Isolation Forest

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/AnomalyScore.R

Return anomaly scores and path length of x according to forest.

1	AnomalyScore(x, forest, ntree = forest$ntree, hlim = forest$hlim, appRange = F)

`x`	a data frame of samples
`forest`	an object generated by `IsolationTrees()`
`ntree`	specifies the number of trees used to find the anomaly score, must be greater than 0 and smaller or equal to number of tree used in the model
`hlim`	evaluation tree height limit
`appRange`	boolean switch to apply application range

AnomalyScore passes each sample in x through forest to obtain expected path length. It then uses path length and parameter in forest to determine anomaly score.

`outF`	anomaly scores of samples in `x`
`pathLength`	average path lengths of samples in `x`

Fei Tony Liu

Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou
Isolation Forest
IEEE International Conference on Data Mining 2008 (ICDM 08), Pisa, Italy, 2008. http://www.gscit.monash.edu.au/gscitweb/loid.php?loid=905282&mimetype=application/pdf

IsolationTrees

library(IsolationForest)
data(stackloss)
# train a model of Isolation Forest
tr<-IsolationTrees(stackloss,rFactor=0)
#evaluate anomaly score
as<-AnomalyScore(stackloss,tr)
# show anomaly score
as$outF