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1. IDENTIFICACIÓN DE CANDIDATOS A PRIMOS DE MERSENNE MEDIANTE CLASIFICACIÓN OVA-ANGULAR UTILIZANDO APRENDIZAJE AUTOMÁTICO CON REGRESIÓN SVM Y KERNEL GAUSSIANO.

Author

Acevedo, Y. and Loaiza, G.

Subjects
*SUPPORT vector machines, *PRIME numbers, *PROGRAMMING languages, *MACHINE learning, *ALGORITHMS
Abstract

In this paper three prime numbers are presented as high potentials to be Mersenne numbers and their application in computational primality testing is suggested. These numbers are constructed from a regression algorithm based on Support vector machines (SVM) and using a Gaussian Kernel. Data training is carried out using the Phyton programming language, In the study we address the current data of Mersenne primes and work with the Ova-angular classification group for Mersenne primes 31. [ABSTRACT FROM AUTHOR]

Published
2023
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