A comparison of fitness-case sampling methods for symbolic regression with genetic programming

Yuliana Martinez; Leonardo Trujillo; Enrique Naredo; Pierrick Legrand

doi:10.1007/978-3-319-07494-8_14

Conference papers

A comparison of fitness-case sampling methods for symbolic regression with genetic programming

Yuliana Martinez ¹ Leonardo Trujillo ¹ Enrique Naredo ¹ Pierrick Legrand ^{2, 3}

1 Instituto Tecnológico de Tijuana

2 CQFD - Quality control and dynamic reliability

IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest

3 IMB - Institut de Mathématiques de Bordeaux

Document type :

Conference papers

Domain :

Computer Science [cs] / Signal and Image Processing

Engineering Sciences [physics] / Signal and Image processing

Computer Science [cs] / Artificial Intelligence [cs.AI]

Complete list of metadata

https://hal.inria.fr/hal-01060313
Contributor : Pierrick Legrand Connect in order to contact the contributor
Submitted on : Wednesday, September 3, 2014 - 1:47:36 PM
Last modification on : Saturday, December 4, 2021 - 3:43:00 AM

A comparison of fitness-case sampling methods for symbolic regression with genetic programming

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A comparison of fitness-case sampling methods for symbolic regression with genetic programming

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