Classification Trees vs. Logistic Regression in the Generic Skill Development in Engineering

Authors

  • Jorge Pérez Rave Grupo de investigación IDINNOV, IDINNOV S.A.S
  • Favián González Echavarría Universidad de Antioquia, Departamento de Ingeniería Industrial, Facultad de Ingeniería

DOI:

https://doi.org/10.13053/cys-22-4-2804

Keywords:

Logistic regression, classification tree, engineering skills

Abstract

From an experimental approach, the performance of Logistic Regression vs Classification Trees is evaluated in the context of two generic engineering skills (quantitative reasoning and reading comprehension). These methods incorporate two separate predictor scenarios (indicators only, and only constructs derived from Principal Component Analysis: ACP). The sample is 7,395 instances of Saber Pro 2015-3, 2014-3 (Colombia). The study considers: training (70% of the sample), prediction (30% remaining) and experimentation (176 original observations, design of three factors: method, type of predictor and competence). The response variable is a new metric (Underlying Asset Ratio obtained by ACP). Both methods present similar performance in the scenario of only indicators, but not in the scenario of constructs (Regression Logistics, better performance).

Author Biography

Jorge Pérez Rave, Grupo de investigación IDINNOV, IDINNOV S.A.S

Ingeniero Industrial de la Universidad de Antioquia (Colombia). Especialista en Sistemas, Especialista en Estadística y Magíster en Ingeniería de Sistemas de la Universidad Nacional de Colombia. Investigador, consultor, emprendedor, autor de cinco libros y de varios artículos publicados en revistas de carácter nacional e internacional. Entre sus reconocimientos, están: Desempeño destacado en asesoramiento y coordinación del curso "Ruta de la mejora continua..., 2016" - Grupo de Gestión Logística UdeA. Director de proyecto de consultoría calificado con beneficio tributario, Colciencias (2015). Premio Mejor evaluación 2012 - Centro de Información Tecnológica (Chile); Premio a la investigación docente 2011 Facultad de Ingeniería de la Universidad de Antioquia. Actualmente, culminando Máster en Análisis-Visualización de Big Data (en evaluación de tesis) y realizando estudios doctorales, y dirigiendo el grupo de investigación IDINNOV.

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Published

2018-12-30

Issue

Vol. 22 No. 4 (2018): Topic Trends in Computing Research (Guest Editors: A. Aguilar-Meléndez, E. Moya-Sánchez)

Section

Articles

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