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Erschienen in:
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2024 | OriginalPaper | Buchkapitel

11. Bioinformatics Research Based on Evolutionary Computation

verfasst von : Qingfeng Chen

Erschienen in: Association Analysis Techniques and Applications in Bioinformatics

Verlag: Springer Nature Singapore

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Abstract

Evolutionary computation-based association analysis has achieved significant progress in the field of data mining. This research approach fully leverages the advantages of evolutionary computation in global search and optimization, enhancing the efficiency and accuracy of association rule mining. The key of evolutionary computation methods lies in transforming association analysis problems into optimization problems. By doing so, the optimal association rules can be sought within the space of association rules. To achieve this objective, researchers need to define fitness functions to evaluate the quality of association rules, such as support and confidence measures. Additionally, evolutionary computation algorithms require settings for population initialization, selection, mutation, and other operations to effectively explore the search space.

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Vorheriges Kapitel Fusion and Radiomics Study of Multimodal Medical Images
Nächstes Kapitel Relationship Prediction Based on Complex Network
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Metadaten
Titel
Bioinformatics Research Based on Evolutionary Computation
verfasst von
Qingfeng Chen
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
Buch
Association Analysis Techniques and Applications in Bioinformatics

Print ISBN: 978-981-9982-50-9

Electronic ISBN: 978-981-9982-51-6

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-981-99-8251-6_11

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