Autor: Diana Chamorro

Director: Diego Peluffo

Universidad de las Fuerzas Armadas, Sangolquí - Ecuador 2019

Official link: http://repositorio.espe.edu.ec/jspui/handle/21000/21822

Data mining is widely used in several fields, such as: education, mobile computing, web mining, financial analysis, crime analysis, engineering, management, and medicine, among others. Naturally, in the dynamics of today's society, education and research have become increasingly important. Furthermore, educational institutions are generating and storing students’ data, which –undergoing an appropriate, subsequent processing- can be useful to make strategic decisions in favor of all the internal academic processes thereof. In this sense, computerized techniques, particularly data mining techniques, have become a key tool since they allow students for a better understanding, as well as identifying the environments in which they learn, by guiding the institutions on how to proceed to provide continuous improvements in reaching the high quality in education.

This master’s thesis presents a study of data mining techniques -applied to data of students from secondary education- to propose a conceptual and algorithmic basis to design a tool having a greater margin of analysis of the information. Specifically, the explored methods are: weighted nearest neighbors, decision trees, support vector machines, and multi-classifier approaches.

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