Predictive change point detection for heterogeneous data

arXiv:2305.06630v3 Announce Type: replace
Abstract: A change point detection (CPD) framework assisted by a predictive machine learning model called "Predict and Compare" is introduced and characterised in relation to other state-of-the-art online CPD routines which it outperforms in terms of false positive rate and out-of-control average run length. The method's focus is on improving standard methods from sequential analysis such as the CUSUM rule in terms of these quality measures.
This is achieved by replacing typically used trend estimation functionals …

abstract art arxiv change control cs.lg data detection false focus framework machine machine learning machine learning model positive predictive rate state terms type