Func.trans: Outlier score transformation

In HighDimOut: Outlier Detection Algorithms for High-Dimensional Data

Description

This function calculate the transformed outlier scores, with the aim of unifying the results from different methods. The method is based on the work of Kriegel, H.P., Kroger, P., Schubert, E., Zimek, A., Interpreting and unifying outlier scores, 2011. It consists of two steps, regularization and normalization. For the ABOD scores, logarithmic inversion is used for regularization For the SOD scores, no action is taken to perform regularization For the FBOD method, the basic regularization, i.e., score-1, is used for regularization For the normalization step, the gaussian scaling method is used. The final output can be interpreted as the outlier probability, ranging from 0 to 1.

Usage

Func.trans(raw.score, method)

Arguments

raw.score	is the scores returned by each method
method	should be a character specifying the method used to generate the raw score. It has 3 possible values, "ABOD", "SOD", and "FBOD".

Value

The function returns the transformed outlier scores

HighDimOut documentation built on May 2, 2019, 12:16 p.m.