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Dataset Open Access

Psychosocial Risk Level Teachers School Repository 2016-2017

Rodolfo Mosquera

Researcher(s)
Rodolfo Mosquera; Omar Danilo Castrillón Gómez; Liliana Parra Osorio

The database was created with 5344 records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.

The repository contains two datasets, one of the total population and a sample of the population to which associated physiological variables were evaluated. 1. The First dataset: -- Number of Instances: 5444 -- Number of Attributes: 115 (114 predictive attributes, 1 class) The second dataset --Number of instances: 481 --Number of attributes: 120 (119 predictive attributes, 1 class)
Files (1.6 MB)
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1.Repository_ABS_TEXT.docx
md5:e252ae36583eb586b7f8df92244722b4
40.5 kB Download
Psychosocial Risk Assessment Level Colombian Teachers School HR, EDA, EMG.csv
md5:2de5b4741d6c62a7905ed8692a4c3b60
146.2 kB Download
Psychosocial Risk Assessment Level Colombian Teachers School.csv
md5:cacd573128074c74ada663f6d6f2cb07
1.4 MB Download
  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2018). Support Vector Machines, Naïve Bayes Classifier and Genetic Algorithms for the Prediction of Psychosocial Risks in Teachers of Colombian Public Schools. Inf. tecnol. vol.29, n.6, pp.153-162. http://dx.doi.org/10.4067/S0718-07642018000600153.

  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2018). Prediction of Psychosocial Risks in Colombian Teachers of Public Schools using Machine Learning Techniques. Inf. tecnol. vol.29, n.4, pp.267-280. http://dx.doi.org/10.4067/S0718-07642018000400267.

  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2016). Methodology for Predicting the Psychosocial Risk Level on Colombian Teachers using Data Mining Techniques. Inf. tecnol. vol.27, n.6, pp.259-272. http://dx.doi.org/10.4067/S0718-07642016000600026.

  • Mosquera Navarro, R., Castrillón, O. D. G., Osorio, L. P., & García, A. C. (2018). Classification system for the predicting of psychosocial risk level in public-school teachers based on Artificial Intelligence. XVIII Conferencia de La Asociación Española Para La Inteligencia Artificial (CAEPIA), 1367-1372.

  • Mosquera, R, Castrillón Gómez, O. D., & Parra-Osorio, L. (2019a). A new method based on Physical Surface Tension-Neural Net for the Prediction of Psychosocial-risk Level in Public School Teachers. (Versión 1) [Matlab]. Recuperado de https://doi.org/10.24433/CO.4268666.v1

  • Mosquera, R, Castrillón Gómez, O. D., & Parra-Osorio, L. (2019b). Aplicación del modelo hibrido k-nearest neighbors-Support Vector Machine para la predicción del riesgo psicosocial en docentes de colegios públicos colombianos. Presentado en 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, And Infrastructure for Sustainable Cities and Communities", Jamaica. Recuperado de http://www.laccei.org/index.php/publications/laccei-proceedings

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