CHANGE-POINT DETECTION WITH SUPERVISED LEARNING AND FEATURE SELECTION

Victor Eruhimov, Vladimir Martyanov, Eugene Tuv, George C. Runger

2007

Abstract

Data streams with high dimensions are more and more common as data sets become wider. Time segments of stable system performance are often interrupted with change events. The change-point problem is to detect such changes and identify attributes that contribute to the change. Existing methods focus on detecting a single (or few) change-point in a univariate (or low-dimensional) process. We consider the important high-dimensional multivariate case with multiple change-points and without an assumed distribution. The problem is transformed to a supervised learning problem with time as the output response and the process variables as inputs. This opens the problem to a wide set of supervised learning tools. Feature selection methods are used to identify the subset of variables that change. An illustrative example illustrates the method in an important type of application.

Paper Citation

in Harvard Style

Eruhimov V., Martyanov V., Tuv E. and C. Runger G. (2007). CHANGE-POINT DETECTION WITH SUPERVISED LEARNING AND FEATURE SELECTION . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-972-8865-82-5, pages 359-363. DOI: 10.5220/0001631303590363

in Bibtex Style

@conference{icinco07,
author={Victor Eruhimov and Vladimir Martyanov and Eugene Tuv and George C. Runger},
title={CHANGE-POINT DETECTION WITH SUPERVISED LEARNING AND FEATURE SELECTION},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2007},
pages={359-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001631303590363},
isbn={978-972-8865-82-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - CHANGE-POINT DETECTION WITH SUPERVISED LEARNING AND FEATURE SELECTION
SN - 978-972-8865-82-5
AU - Eruhimov V.
AU - Martyanov V.
AU - Tuv E.
AU - C. Runger G.
PY - 2007
SP - 359
EP - 363
DO - 10.5220/0001631303590363