SciELO - Scientific Electronic Library Online

 
vol.29 número4Percepciones de Estudiantes de Nivel Secundaria sobre el uso de las TIC en su Clase de CienciasUna Revisión de los Estimadores de Matrices de Bajo Rango y Matrices Dispersas índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Información tecnológica

versión On-line ISSN 0718-0764

Resumen

MOSQUERA, Rodolfo; CASTRILLON, Omar D.  y  PARRA, Liliana. Prediction of Psychosocial Risks in Colombian Teachers of Public Schools using Machine Learning Techniques. Inf. tecnol. [online]. 2018, vol.29, n.4, pp.267-280. ISSN 0718-0764.  http://dx.doi.org/10.4067/S0718-07642018000400267.

This paper presents a new methodology based on machine learning techniques in diagnostics of psychosocial assessments to identify the risk level in teachers of public schools in Colombia. A comparative study of three important models of machine learning for prediction was done: artificial neural networks, decision trees and naive bayes, reducing the dimensionality of the data. This was done by applying genetic algorithms, algorithm of the expected amount of information, the algorithm GainRatioAttributeEval, Pearson's relation coefficient and principal components analysis. A database was used with 5340 epidemiological records, corresponding to psychosocial evaluations of teachers from public schools in the metropolitan area of ​​a Colombian city. The best predictive performance was obtained with the model of artificial neural networks with an accuracy 93%.

Palabras clave : machine learning; artificial neural network; genetic algorithm; principal components analysis.

        · resumen en Español     · texto en Español     · Español ( pdf )