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发表于 2025-3-21 18:41:16 | 显示全部楼层 |阅读模式
书目名称Grammatical Inference
编辑Wojciech Wieczorek
视频video
丛书名称Studies in Computational Intelligence
图书封面Titlebook: ;
出版日期Book 2017
版次1
doihttps://doi.org/10.1007/978-3-319-46801-3
isbn_softcover978-3-319-83589-1
isbn_ebook978-3-319-46801-3Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
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D. J. Benos,D. G. Warnock,J. B. Smith changed or fixed, plays the crucial role. The following two approaches are presented: Error-Correcting Grammatical Inference (EGCI) and Alignment-Based Learning (ABL). The former approach incrementally grows an inferred automaton by explicitly minimizing (with the help of dynamic programming) the n
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Teubner Studienbücher der Biologiee for lexicon representation and fast string matching, and it may have a variety of applications as well. Since a DAWG is acyclic the proposed method is suited for GI problems where the target language does not necessarily have to be infinite. The results of experiments showed in the next chapter fo
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https://doi.org/10.1007/978-3-319-45315-6 data. We show how to apply: (1) mathematical modeling in discovery of ordinary generating functions, (2) a decomposition-based approach: (a) to minimize boolean functions (b) to improve combinatorial game performance, and (c) in classification of biological sequences. The overall thrust of the firs
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State Merging Algorithms, presented: evidence driven state merging, Gold’s algorithm, and an algorithm based on the minimum description length principle. Their common denominator is the merging of two states. All differences result from various particular reasons for choosing the pair of states to do this operation.
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