Data Mining Tool for Academic Data Exploitation : Selection of most suitable Algorithms
López Vicario, José (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Vilanova i Arbós, Ramon (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Bazzarelli, Manuela (Politecnico de Milano)
Paganoni, Anna Maria (Politecnico de Milano)
Spagnolini, Umberto (Politecnico de Milano)
Torrebruno, Aldo (Politecnico de Milano)
Prada Medrano, Miguel Ángel (Universidad de León)
Morán, Antonio (Universidad de León)
Domínguez González, Manuel (Universidad de León)
Varanda, Maria João (Instituto Politecnico de Bragança)
Alves, P. (Instituto Politecnico de Bragança)
Popdora, Michal (Opole University of Technology)
Barbu, Marian (University of Galati)

Fecha:	2018
Descripción:	53 pàg.
Resumen:	This document aims to reflect the results obtained at SPEET project under the development of the data mining tools are presented. More specifically, two mechanisms have been developed: a clustering/classification scheme of students in terms of academic performance and a drop-out prediction system. The students' clustering and classification schemes are presented in detail. More specifically, a description of the considered machine learning algorithms can be found. Results show how groups of clusters can be automatically identified and how new students can be classified into existing groups with a high accuracy. Finally, the implemented drop-out prediction system is considered by presenting several algorithms alternatives. In this case, the evaluation of the dropout mechanism is focused on one institution, showing a prediction accuracy around 91 %. Algorithms presented at this document are available at repositories or inline code format, as accordingly indicated.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Colección:	SPEET project Intellectual Outputs
Documento:	Llibre
Materia:	Educational data-mining ; Student performance ; Drop-out
ISBN:	978-989-20-8738-2

57 p, 3.1 MB

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