Combining genetic algorithm and support vector machine for classification of cancer on microarray data
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Author (Corporation)
Publication date
2023
Type 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
Related research data
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-reviewed
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