Combining genetic algorithm and support vector machine for classification of cancer on microarray data
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Author (Corporation)
Publication date
2023
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editor (Corporation)
Supervisor
Parent work
Soft Computing: Theories and Applications. Proceedings of SoCTA 2022
Special issue
DOI of the original publication
Series
Lecture Notes in Networks and Systems
Series number
627
Volume
Issue / Number
Pages / Duration
527-537
Patent number
Publisher / Publishing institution
Springer
Place of publication / Event location
Shimla
Edition
Version
Programming language
Assignee
Practice partner / Client
Keywords
Event
7th International Conference on Soft Computing: Theories and Applications (SoCTA 2022)
Exhibition start date
Exhibition end date
Conference start date
16.12.2022
Conference end date
18.12.2022
Date of the last check
ISBN
978-981-19-9857-7
978-981-19-9858-4
978-981-19-9858-4
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Dornberger, R., Hanne, T., & Plagemann, T. (2023). Combining genetic algorithm and support vector machine for classification of cancer on microarray data. In R. Kumar, A. K. Verma, T. K. Sharma, O. P. Verma, & S. Sharma (Eds.), Soft Computing: Theories and Applications. Proceedings of SoCTA 2022 (pp. 527–537). Springer. https://doi.org/10.1007/978-981-19-9858-4_45