Variables characterization by using computing intelligence to identify the cattle s health disorders

Detecting disorders in lab tests applied in animals is a complex process that implies linking different variables and clinical factors of the individuals. lt is why during the development of the present research, some computing intelligence techniqueswere evaluated, which contributed to the behavior patterns identification of the most important disorders detected in CBC tests applied in cattle, Although several computing intelligence algorithms are used in medical troubleshooting, no record of researches in veterinary medical processes was found. Once the thorough characterization of the variables and the evaluation of the computing intelligence techniques were made, it was determined that the algorithm that best fits to the purpose of the proposed data analysis is FP-Growth.

• Fecha de publicación: 2015
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10542
• Acceso en línea: https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/4112; https://repositorio.uptc.edu.co/handle/001/10542
• Palabra clave: data analysis; algorithms; animal health; FP—growth.; Análisis de datos; Algoritmos; Sanidad animal; FP-Growth
• License: Copyright (c) 2015 CIENCIA Y AGRICULTURA