Bayesian classifier applied to higher education dropout
Clasificador bayesiano aplicado al abandono de la educación superior
| dc.creator | Amelec, Viloria | |
| dc.creator | Pineda Lezama, Omar Bonerge | |
| dc.creator | Varela Izquierdo, Noel | |
| dc.date.accessioned | 2020-02-03T19:28:28Z | |
| dc.date.available | 2020-02-03T19:28:28Z | |
| dc.date.issued | 2019 | |
| dc.identifier.issn | 00002010 | |
| dc.identifier.uri | http://hdl.handle.net/11323/5977 | |
| dc.description.abstract | The research proposes a new simple Bayesian classifier (SBND) with Markov from the class variable to a network structure. Experimental tests are carried out by working a dropout analysis on students enrolled in the Faculty of Engineering Sciences of Mumbai University, in India in the period 2017-2018 on the basis of socioeconomic data. The Weka tool is then used to perform the classification and the proposed model is statistically compared with other Bayesian classifiers. | spa |
| dc.description.abstract | La investigación propone un nuevo clasificador bayesiano simple (SBND) con Markov de la variable de clase a una estructura de red. Las pruebas experimentales se llevan a cabo mediante un análisis de abandono en los estudiantes matriculados en la Facultad de Ciencias de la Ingeniería de la Universidad de Mumbai, en la India, en el período 2017-2018 sobre la base de datos socioeconómicos. La herramienta Weka se utiliza para realizar la clasificación y el modelo propuesto se compara estadísticamente con otros clasificadores bayesianos. | spa |
| dc.language.iso | eng | spa |
| dc.publisher | Procedia Computer Science | spa |
| dc.rights | CC0 1.0 Universal | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.subject | Bayesian networks | spa |
| dc.subject | Bayesian classifier | spa |
| dc.subject | Educational analysis | spa |
| dc.subject | Redes bayesianas | spa |
| dc.subject | Clasificacion bayesiana | spa |
| dc.subject | Analisis educacional | spa |
| dc.title | Bayesian classifier applied to higher education dropout | spa |
| dc.title.alternative | Clasificador bayesiano aplicado al abandono de la educación superior | spa |
| dc.type | Article | spa |
| dcterms.references | Torres-Samuel, M., Vásquez, C., Viloria, A., Lis-Gutiérrez, J.P., Borrero, T.C., Varela, N.: Web Visibility Profiles of Top100 Latin American Universities. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, Springer, Cham, vol 10943, 1-12 (2018). | spa |
| dcterms.references | Zhang, G.P.: Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50 (1), 159-75 (2003). | spa |
| dcterms.references | Duan, L., Xu, L., Liu, Y., Lee, J.: Cluster-based outlier detection. Annals of Operations Research 168 (1), 151–168 (2009). | spa |
| dcterms.references | Haykin, S.: Neural Networks a Comprehensive Foundation. Second Edition. Macmillan College Publishing, Inc. USA. ISBN 9780023527616 (1999). | spa |
| dcterms.references | Haykin, S.: Neural Networks and Learning Machines. New Jersey, Prentice Hall International (2009). | spa |
| dcterms.references | Oviedo, B. a. (2015). Análisis de datos educativos utilizando redes bayesianas, Latin American and Caribbean Conference for Engineering and Technology LACCEI 2015. | spa |
| dcterms.references | Abhay, K. A., Badal, N. A.: Novel Approach for Intelligent Distribution of Data Warehouses. Published in Egyptian Informatics JournalElsevier, Egypt 17 (1), 147-159, (October, 2015). | spa |
| dcterms.references | Vasquez, C., Torres, M., Viloria, A.: Public policies in science and technology in Latin American countries with universities in the top 100 of web ranking. J. Eng. Appl. Sci. 12(11), 2963–2965 (2017). | spa |
| dcterms.references | Vásquez, C., Torres-Samuel, M., Viloria, A., Lis-Gutiérrez, J.P., Crissien Borrero, T., Varela, N., Cabrera, D.: Cluster of the Latin American Universities Top100 According to Webometrics 2017. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, Springer, Cham, vol 10943, 1-12 (2018). | spa |
| dcterms.references | Sevim, C., Oztekin, A., Bali, O., Gumus, S., Guresen, E.: Developing an early warning system to predict currency crises. European Journal of Operational Research 237(1), 1095-104 (2014). | spa |
| dcterms.references | Viloria, A., Lis-Gutiérrez, J.P., Gaitán-Angulo, M., Godoy, A.R.M., Moreno, G.C., Kamatkar, S.J.: Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching – Learning Process Through Knowledge Data Discovery (Big Data). In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. | spa |
| dcterms.references | Soca, E.B., El trabajo independiente en el proceso de enseñanza-aprendizaje, ISSN: 1684-1859, Revista Cubana de Informática Médica, 7(2), 122-131 (2015) | spa |
| dcterms.references | Vanyolos, E., I. Furka, I. Miko y otros tres autores. How does practice improve the skills of medical students during consecutive training courses? doi; https://dx.doi.org/10.1590/s0102-865020170060000010. Rev. Acta Cirurgica Brasileira, 32(6), 491-502 (2017) | spa |
| dcterms.references | Isasi, P., Galván, I.: Redes de Neuronas Artificiales. Un enfoque Práctico. Pearson. ISBN 8420540250 (2004). | spa |
| dcterms.references | Haykin, S.: Neural Networks and Learning Machines. New Jersey, Prentice Hall International (2009). | spa |
| dc.type.hasVersion | info:eu-repo/semantics/submittedVersion | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
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