Methodology for the use of machine learning, applied in predicting the level of success in legal cases

• Autores: Rojas Romero, Karin Corina, Auccahuasi, Wilver, Herrera, Lucas, Urbano, Kitty, Peláez, Brayan, Flores Peña, Pedro, Montes Osorio, Yuly, Bernardo, Grisi, Bernardo, Madelaine, Meza, Sandra, Ovalle, Christian, Hilario, Francisco, Liendo, Milner, Sernaque, Fernando
• Formato: objeto de conferencia
• Fecha de Publicación: 2022
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/5778
• Enlace del recurso: https://hdl.handle.net/20.500.12867/5778
• Nivel de acceso: acceso abierto
• Materia: Machine learning; Legal procedure; https://purl.org/pe-repo/ocde/ford#2.02.04

ICTs have allowed the applications of artificial intelligence to grow exponentially, where different applications are being presented, based on the application of neural networks as prediction mechanisms for different processes and applications, in the present work the use of the Neural networks for the legal case prediction process, in which the analysis of approximately 200 cases was used between cases that had "positive and negative" final results, the expected results after implementing the solution in the MATLAB tool, they presented us effectiveness results in a value of 93%, as a conclusion we can indicate that the model provided allows us to be applied in other conditions as well as to be scaled, taking into account the historical data that may be available for the training process.