One-step or two-step optimization and the overfitting phenomenon: A case study on time series classification

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

1 Citation (Scopus)

Abstract

For the last few decades, optimization has been developing at a fast rate. Bio-inspired optimization algorithms are metaheuristics inspired by nature. These algorithms have been applied to solve different problems in engineering, economics, and other domains. Bio-inspired algorithms have also been applied in different branches of information technology such as networking and software engineering. Time series data mining is a field of information technology that has its share of these applications too. In previous works we showed how bio-inspired algorithms such as the genetic algorithms and differential evolution can be used to find the locations of the breakpoints used in the symbolic aggregate approximation of time series representation, and in another work we showed how we can utilize the particle swarm optimization, one of the famous bio-inspired algorithms, to set weights to the different segments in the symbolic aggregate approximation representation. In this paper we present, in two different approaches, a new meta optimization process that produces optimal locations of the breakpoints in addition to optimal weights of the segments. The experiments of time series classification task that we conducted show an interesting example of how the overfitting phenomenon, a frequently encountered problem in data mining which happens when the model overfits the training set, can interfere in the optimization process and hide the superior performance of an optimization algorithm.

Original languageEnglish
Title of host publicationICAART 2014 - Proceedings of the 6th International Conference on Agents and Artificial Intelligence
PublisherSciTePress
Pages645-650
Number of pages6
ISBN (Print)9789897580154
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event6th International Conference on Agents and Artificial Intelligence - Angers, Loire Valley, France
Duration: 6 Mar 20148 Mar 2014

Publication series

NameICAART 2014 - Proceedings of the 6th International Conference on Agents and Artificial Intelligence
Volume1

Conference

Conference6th International Conference on Agents and Artificial Intelligence
Abbreviated titleICAART 2014
CountryFrance
CityAngers, Loire Valley
Period6/03/148/03/14

Keywords

  • Bio-inspired optimization
  • Differential evolution
  • Overfitting
  • Time series classification

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Fuad, M. M. M. (2014). One-step or two-step optimization and the overfitting phenomenon: A case study on time series classification. In ICAART 2014 - Proceedings of the 6th International Conference on Agents and Artificial Intelligence (pp. 645-650). (ICAART 2014 - Proceedings of the 6th International Conference on Agents and Artificial Intelligence; Vol. 1). SciTePress.