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- W4285805497 abstract "In this paper we compare performance of genetic programming-based symbolic classifiers on a novel synthetic machine learning benchmark called DIGEN. This framework and collection of 40 different classification problems was designed specifically to differentiate performance of leading machine learning methods." @default.
- W4285805497 created "2022-07-19" @default.
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- W4285805497 date "2022-07-09" @default.
- W4285805497 modified "2023-10-09" @default.
- W4285805497 title "A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark" @default.
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- W4285805497 doi "https://doi.org/10.1145/3520304.3529056" @default.
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