| 期刊全称 | Automating the Design of Data Mining Algorithms | | 期刊简称 | An Evolutionary Comp | | 影响因子2023 | Gisele L. Pappa,Alex Freitas | | 视频video | | | 发行地址 | This book proposes a different goal for evolutionary algorithms in data mining: to automate the design of a data mining algorithm, rather than just optimize its parameters..Includes supplementary mate | | 学科分类 | Natural Computing Series | | 图书封面 |  | | 影响因子 | Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from dat | | Pindex | Book 2010 |
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发表于 2025-3-21 19:52:48
