- author = "Alex G. C. {de Sa} and Walter Jose G. S. Pinto and Luiz Otavio V. B. Oliveira and Gisele Pappa",
- title = "{RECIPE}: A Grammar-based Framework for Automatically Evolving Classification Pipelines",
- booktitle = "EuroGP 2017: Proceedings of the 20th European Conference on Genetic Programming",
- year = "2017",
- month = "19-21 " # apr,
- editor = "Mauro Castelli and James McDermott and Lukas Sekanina",
- series = "LNCS",
- volume = "10196",
- publisher = "Springer Verlag",
- address = "Amsterdam",
- pages = "246--261",
- organisation = "species",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-319-55695-6",
-
code_url = "
https://github.com/laic-ufmg/Recipe",
-
DOI = "
doi:10.1007/978-3-319-55696-3_16",
- abstract = "Automatic Machine Learning is a growing area of machine learning that has a similar objective to the area of hyper-heuristics: to automatically recommend optimized pipelines, algorithms or appropriate parameters to specific tasks without much dependency on user knowledge. The background knowledge required to solve the task at hand is actually embedded into a search mechanism that builds personalized solutions to the task. Following this idea, this paper proposes RECIPE (REsilient ClassifIcation Pipeline Evolution), a framework based on grammar-based genetic programming that builds customized classification pipelines. The framework is flexible enough to receive different grammars and can be easily extended to other machine learning tasks. RECIPE overcomes the drawbacks of previous evolutionary-based frameworks, such as generating invalid individuals, and organizes a high number of possible suitable data pre-processing and classification methods into a grammar. Results of f-measure obtained by RECIPE are compared to those two state-of-the-art methods, and shown to be as good as or better than those previously reported in the literature. RECIPE represents a first step towards a complete framework for dealing with different machine learning tasks with the minimum required human intervention.",
-
notes = "cites \cite{Olson:2016:GECCO}
Also known as desa2017recipe
Part of \cite{Castelli:2017:GP} EuroGP'2017 held inconjunction with EvoCOP2017, EvoMusArt2017 and EvoApplications2017",
