Exploring the efficiency : A comprehensive analysis of machine learning algorithms in WEKA software
*Nikhil KambleCorresponding authorkamblenb22.comp@coep.ac.inDepartment of Computer Engineering & Information TechnologyShivajinagarCOEP Technological UniversityPune, Maharashtra, 411005, IndiaView full profile → , Atharva Phatakbe21b009@smail.iitm.ac.inDepartment of BiotechnologyIndian Institute of TechnologyMadras, Chennai, 600036, IndiaView full profile → , Aaryan JoshiS-2101100@moderncollegepune.ac.inDepartment of Computer ScienceProgressive Education Society’s, ShivajinagarModern College of Arts, Science and CommercePune, Maharashtra, 411005, IndiaView full profile → , Rahul Adhaorba.comp@coep.ac.inSchool of Computer EngineeringAlandiMIT Academy of EngineeringPune, Maharashtra, 412105, IndiaView full profile → , Vinod Pachgharevkp.comp@coep.ac.inDepartment of Computer Engineering & Information TechnologyShivajinagarCOEP Technological UniversityPune, Maharashtra, 411005, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 06 May 2024
- Published Online:
- 05 Aug 2024
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JSMS-1299
- Pages:
- 1009–1019
Abstract
Keywords
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References
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[11] Witten, Ian & Hall, Mark & Frank, Eibe & Holmes, Geoffrey & Pfahringer, Bernhard & Reutemann, Peter. The WEKA data mining software: An update. SIGKDD Explorations. 11. 10-18 (2009). 10.1145/1656274.1656278.
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