poster

An estimation distribution algorithm with the spearman's rank correlation index

Authors:

Arturo Hernández-Aguirre,

Enrique Villa-Diharce,

Selma Barba-MorenoAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 469 - 470

https://doi.org/10.1145/1389095.1389182

Published: 12 July 2008 Publication History

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Abstract

This article arguments that rank correlation coefficients are powerful association measures and how can they be adopted by EDAs. A new EDA implements the proposed ideas: the Non-Parametric Real-valued Estimation Distribution Algorithm (NOPREDA). The paper fully describes the rank correlation coefficient, and the procedure to build a non parametric model for the probability distribution of the source data. A benchmark of global optimization problems is solved with NOPREDA.

References

[1]

J. Grahl, P. A. N. Bosman, and F. Rothlauf. The correlation-triggered adaptive variance scaling IDEA. In GECCO '06: Proceedings of the 8th annual conference on Genetic and Evolutionary Computation, pages 397--404. ACM Press, 2006.

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[2]

R. L. Iman and W. J. Conover. A distribution-free approach to inducing rank correlation among input variables. Communications in Statistics: Simulation and Computation, 11(3):311--334, 1982.

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Albahli SNazir TNawaz MIrtaza A(2023)An improved DenseNet model for prediction of stock market using stock technical indicatorsExpert Systems with Applications10.1016/j.eswa.2023.120903232(120903)Online publication date: Dec-2023
https://doi.org/10.1016/j.eswa.2023.120903
Albahli SNazir TMehmood AIrtaza AAlkhalifah AAlbattah W(2022)AEI-DNET: A Novel DenseNet Model with an Autoencoder for the Stock Market Predictions Using Stock Technical IndicatorsElectronics10.3390/electronics1104061111:4(611)Online publication date: 16-Feb-2022
https://doi.org/10.3390/electronics11040611
Nakanishi T(2014)Semantic Context-Dependent Weighting for Vector Space ModelProceedings of the 2014 IEEE International Conference on Semantic Computing10.1109/ICSC.2014.49(262-266)Online publication date: 16-Jun-2014
https://dl.acm.org/doi/10.1109/ICSC.2014.49
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An estimation distribution algorithm with the spearman's rank correlation index
1. Applied computing
  1. Physical sciences and engineering
    1. Mathematics and statistics

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Published In

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

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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Association for Computing Machinery

New York, NY, United States

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Albahli SNazir TNawaz MIrtaza A(2023)An improved DenseNet model for prediction of stock market using stock technical indicatorsExpert Systems with Applications10.1016/j.eswa.2023.120903232(120903)Online publication date: Dec-2023
https://doi.org/10.1016/j.eswa.2023.120903
Albahli SNazir TMehmood AIrtaza AAlkhalifah AAlbattah W(2022)AEI-DNET: A Novel DenseNet Model with an Autoencoder for the Stock Market Predictions Using Stock Technical IndicatorsElectronics10.3390/electronics1104061111:4(611)Online publication date: 16-Feb-2022
https://doi.org/10.3390/electronics11040611
Nakanishi T(2014)Semantic Context-Dependent Weighting for Vector Space ModelProceedings of the 2014 IEEE International Conference on Semantic Computing10.1109/ICSC.2014.49(262-266)Online publication date: 16-Jun-2014
https://dl.acm.org/doi/10.1109/ICSC.2014.49
Scanniello GDistante DRisi M(2008)Using Semantic clustering to enhance the navigation structure of Web sites2008 10th International Symposium on Web Site Evolution10.1109/WSE.2008.4655396(55-64)Online publication date: Oct-2008
https://doi.org/10.1109/WSE.2008.4655396
Totakura SNagendra SIndukuri RVijayasherly V(2008)COSProceedings of the 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing10.1109/SNPD.2008.165(569-573)Online publication date: 6-Aug-2008
https://dl.acm.org/doi/10.1109/SNPD.2008.165
De Lucia AOliveto RZurolo FDi Penta M(2006)Improving Comprehensibility of Source Code via Traceability InformationProceedings of the 14th IEEE International Conference on Program Comprehension10.1109/ICPC.2006.28(317-326)Online publication date: 14-Jun-2006
https://dl.acm.org/doi/10.1109/ICPC.2006.28
De Lucia AFasano FOliveto RTortora G(2005)ADAMS Re-TraceProceedings of the Ninth European Conference on Software Maintenance and Reengineering10.1109/CSMR.2005.7(32-41)Online publication date: 21-Mar-2005
https://dl.acm.org/doi/10.1109/CSMR.2005.7
De Lucia AFasano FOliveto RTortora G(2004)Enhancing an artefact management system with traceability recovery features20th IEEE International Conference on Software Maintenance, 2004. Proceedings.10.1109/ICSM.2004.1357816(306-315)Online publication date: 2004
https://doi.org/10.1109/ICSM.2004.1357816
Li Y(1998)Toward a Qualitative Search EngineIEEE Internet Computing10.1109/4236.7076872:4(24-29)Online publication date: 1-Jul-1998
https://dl.acm.org/doi/10.1109/4236.707687
Li YLopresti DNagy GTomkins A(1996)Validation of Image Defect Models for Optical Character RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/34.48153618:2(99-108)Online publication date: 1-Feb-1996
https://dl.acm.org/doi/10.1109/34.481536

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An improved differential evolution by hybridizing with estimation-of-distribution algorithm

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Limiting spectral distribution of large dimensional Spearman’s rank correlation matrices

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