On the Subject of Identifying Anomalies in Heterogeneous Vector Based Data.

Cousins, Cyrus B.

2015

Description
  • Abstract:This paper is focused novel techniques for the unsupervised anomaly detection algorithm over datasets of real and finite discrete variables, centered around the existing FRaC algorithm. Novel variants of the FRaC algorithm are presented, alongside mathematical justification and empirical evidence to support their use. mFRaC, eFRaC and cFRaC, are introduced here. These techniques have a ... read more
This object is in collection Creator department Thesis Type Subject Genre Permanent URL
ID:
p2677666z
Component ID:
tufts:sd.0000231
To Cite:
TARC Citation Guide    EndNote
Usage:
Detailed Rights