Evaluación de Algoritmos de Clasificación utilizando Validación Cruzada FP #471

Evaluación de Algoritmos de Clasificación utilizando Validación Cruzada

Published in: Industry, Innovation, and Infrastructure for Sustainable Cities and Communities: Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 24-26, 2019
Location of Conference: Montego Bay, Jamaica
Authors: Leticia Laura-Ochoa (Universidad Nacional de San Agustín de Arequipa, PE)
(Universidad Nacional de San Agustín de Arequipa)
Full Paper: #471

Abstract:

Cross validation allows to evaluate the accuracy of the classification algorithms with low error, but has the problem of computational cost versus large volumes of data. In this work, the serial and parallel implementation of leave-one-out and k-fold cross validation techniques is performed using the R software environment. A comparison between the precision and error results obtained with cross validation techniques is presented, as well as the execution time thereof, reducing in the parallel implementation