Comparison in the application of classification methods to determine the mode of transportation of students to access the Rodrigo Facio campus of the Universidad Costa Rica in Montes de Oca, San Jose, Costa Rica - Hernández Vega, Henry (2022)
This work presents the results of an exploratory process where different classification methods were applied to determine the mode of transportation for students to access the Rodrigo Facio campus of the University of Costa Rica. Among the analyzed models are binomial logistic regression, linear discriminant analysis, decision trees, K-closest neighbors, vector support machines and neural networks. A validation was carried out with the K-folds method and a precision higher than 83% was obtained for all the models analyzed. Similarly, the stacking assembly model was applied for the decision tree techniques, K-nearest neighbors, vector support machines, random forests, Bootstrap aggregation, binomial logistic regression, and the potentiation method, obtaining precision values higher than 86% in all cases. The random forest method gives the highest precision.