Algoritmos de clasificación y redes neuronales en la observación automatizada de registros

10Citations
Citations of this article
42Readers
Mendeley users who have this article in their library.

Abstract

The aim of this study is to analyse a set of data got through an on-line platform, using some ranking and knowledge oriented discovery rules techniques. Data mining techniques are applied to obtain a reliable relationship which can show the interest of the users in order to fill rigorously the on-line questionnaire attending to the way they do. Although there are programming techniques which allows us to observe the behaviour of users while filling the survey, current work uses artificial neural networks to predict their behaviour, based on variables obtained from the own survey. The sample is made up of 1,636 participants from different geographical areas and age ranges, obtained anonymously by answering the IPSETA questionnaire which is used for a psychological monitoring of sport talents. The results obtained using the analysis techniques show that females prefer to register on the platform to fill the survey, getting a high reliability (70%).

Cite

CITATION STYLE

APA

González-Ruiz, S. L., Gómez-Gallego, I., Pastrana-Brincones, J. L., & Hernández-Mendo, A. (2015). Algoritmos de clasificación y redes neuronales en la observación automatizada de registros. Cuadernos de Psicologia Del Deporte, 15(1), 31–40. https://doi.org/10.4321/S1578-84232015000100003

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free