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Benchmarking pareto archiving heuristics in the presence of concept drift: diversity versus age

Published: 06 July 2013 Publication History

Abstract

A framework for coevolving genetic programming teams with Pareto archiving is benchmarked under two representative tasks for non-stationary streaming environments. The specific interest lies in determining the relative contribution of diversity and aging heuristics to the maintenance of the Pareto archive. Pareto archiving, in turn, is responsible for targeting data (and therefore champion individuals) as appropriate for retention beyond the limiting scope of the sliding window interface to the data stream. Fitness sharing alone is considered most effective under a non-stationary stream characterized by continuous (incremental) changes. Fitness sharing with an aging heuristic acts as the preferred heuristic when the stream is characterized by non-stationary stepwise changes.

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  • (2023)Evolutionary Ensemble LearningHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_8(205-243)Online publication date: 2-Nov-2023
  • (2017)Properties of a GP active learning framework for streaming data with class imbalanceProceedings of the Genetic and Evolutionary Computation Conference10.1145/3071178.3071213(945-952)Online publication date: 1-Jul-2017
  • (2016)Classifying streaming data using grammar-based immune programming2016 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI.2016.7849969(1-8)Online publication date: Dec-2016
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cover image ACM Conferences
GECCO '13: Proceedings of the 15th annual conference on Genetic and evolutionary computation
July 2013
1672 pages
ISBN:9781450319638
DOI:10.1145/2463372
  • Editor:
  • Christian Blum,
  • General Chair:
  • Enrique Alba
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 06 July 2013

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Author Tags

  1. coevolution
  2. genetic programming
  3. online learning
  4. pareto archiving
  5. streaming data

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  • Research-article

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GECCO '13
Sponsor:
GECCO '13: Genetic and Evolutionary Computation Conference
July 6 - 10, 2013
Amsterdam, The Netherlands

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GECCO '13 Paper Acceptance Rate 204 of 570 submissions, 36%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2023)Evolutionary Ensemble LearningHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_8(205-243)Online publication date: 2-Nov-2023
  • (2017)Properties of a GP active learning framework for streaming data with class imbalanceProceedings of the Genetic and Evolutionary Computation Conference10.1145/3071178.3071213(945-952)Online publication date: 1-Jul-2017
  • (2016)Classifying streaming data using grammar-based immune programming2016 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI.2016.7849969(1-8)Online publication date: Dec-2016
  • (2015)Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine LearningIEEE Computational Intelligence Magazine10.1109/MCI.2014.236989210:1(20-32)Online publication date: 14-Jan-2015
  • (2015)Evolving GP Classifiers for Streaming Data Tasks with Concept Change and Label Budgets: A Benchmarking StudyHandbook of Genetic Programming Applications10.1007/978-3-319-20883-1_18(451-480)Online publication date: 2015
  • (2015)Tapped Delay Lines for GP Streaming Data Classification with Label BudgetsGenetic Programming10.1007/978-3-319-16501-1_11(126-138)Online publication date: 15-Mar-2015
  • (2014)On the application of GP to streaming data classification tasks with label budgetsProceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation10.1145/2598394.2611385(1287-1294)Online publication date: 12-Jul-2014

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