Feature engineering for improving robustness of crossover in symbolic regression

Aliyu Sani Sambo; R. Muhammad Atif Azad; Yevgeniya Kovalchuk; Vivek Padmanaabhan Indramohan; Hanifa Shah

doi:10.1145/3377929.3390078

Feature engineering for improving robustness of crossover in symbolic regression

Aliyu Sani Sambo, R. Muhammad Atif Azad, Yevgeniya Kovalchuk, Vivek Padmanaabhan Indramohan, Hanifa Shah

Birmingham City University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Original language	English
Title of host publication	GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion
Publisher	Association for Computing Machinery
Pages	249-250
Number of pages	2
ISBN (Electronic)	9781450371278
DOIs	https://doi.org/10.1145/3377929.3390078
Publication status	Published (VoR) - 8 Jul 2020
Event	2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico Duration: 8 Jul 2020 → 12 Jul 2020

Publication series

Name	GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

Conference

Conference	2020 Genetic and Evolutionary Computation Conference, GECCO 2020
Country/Territory	Mexico
City	Cancun
Period	8/07/20 → 12/07/20

Keywords

Feature engineering
Genetic programming
Regression

Access to Document

10.1145/3377929.3390078

Cite this

Sambo, A. S., Azad, R. M. A., Kovalchuk, Y., Indramohan, V. P., & Shah, H. (2020). Feature engineering for improving robustness of crossover in symbolic regression. In GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 249-250). (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion). Association for Computing Machinery. https://doi.org/10.1145/3377929.3390078

Sambo, Aliyu Sani ; Azad, R. Muhammad Atif ; Kovalchuk, Yevgeniya et al. / Feature engineering for improving robustness of crossover in symbolic regression. GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, 2020. pp. 249-250 (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion).

@inproceedings{f22b1018598d4a9db6f887316be76547,

title = "Feature engineering for improving robustness of crossover in symbolic regression",

keywords = "Feature engineering, Genetic programming, Regression",

author = "Sambo, \{Aliyu Sani\} and Azad, \{R. Muhammad Atif\} and Yevgeniya Kovalchuk and Indramohan, \{Vivek Padmanaabhan\} and Hanifa Shah",

note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 2020 Genetic and Evolutionary Computation Conference, GECCO 2020 ; Conference date: 08-07-2020 Through 12-07-2020",

year = "2020",

month = jul,

day = "8",

doi = "10.1145/3377929.3390078",

language = "English",

series = "GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion",

publisher = "Association for Computing Machinery",

pages = "249--250",

booktitle = "GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion",

}

Sambo, AS, Azad, RMA, Kovalchuk, Y, Indramohan, VP & Shah, H 2020, Feature engineering for improving robustness of crossover in symbolic regression. in GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, pp. 249-250, 2020 Genetic and Evolutionary Computation Conference, GECCO 2020, Cancun, Mexico, 8/07/20. https://doi.org/10.1145/3377929.3390078

Feature engineering for improving robustness of crossover in symbolic regression. / Sambo, Aliyu Sani; Azad, R. Muhammad Atif; Kovalchuk, Yevgeniya et al.
GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, 2020. p. 249-250 (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Feature engineering for improving robustness of crossover in symbolic regression

AU - Sambo, Aliyu Sani

AU - Azad, R. Muhammad Atif

AU - Kovalchuk, Yevgeniya

AU - Indramohan, Vivek Padmanaabhan

AU - Shah, Hanifa

PY - 2020/7/8

Y1 - 2020/7/8

KW - Feature engineering

KW - Genetic programming

KW - Regression

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U2 - 10.1145/3377929.3390078

DO - 10.1145/3377929.3390078

M3 - Conference contribution

AN - SCOPUS:85089751695

T3 - GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

SP - 249

EP - 250

BT - GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

PB - Association for Computing Machinery

T2 - 2020 Genetic and Evolutionary Computation Conference, GECCO 2020

Y2 - 8 July 2020 through 12 July 2020

ER -

Sambo AS, Azad RMA, Kovalchuk Y, Indramohan VP, Shah H. Feature engineering for improving robustness of crossover in symbolic regression. In GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery. 2020. p. 249-250. (GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion). doi: 10.1145/3377929.3390078

Feature engineering for improving robustness of crossover in symbolic regression

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