Towards an automatic detection system of sports talents; an approach to Tae Kwon Do

 

Authors
Estévez Salazar, Alexis Darío
Format
Article
Status
publishedVersion
Description

Tae Kwon Do is a Korean martial art and Olympic combat sport, which is characterized by amazing techniques of kicking. In this sense, it is possible to extract different features of this sport, in this case, we have used well-defined features associates to combat athletes. Herein, we present a support system for national selected athletes team based on feature selection and ranking from Ecuadorian athletes. We use Wrapper and Embedded methods to choose features, which are based on entropy of information and weights of features respectively. For supervised classification, we use two well known algorithms such as Decision Trees and Support Vector Machine. The highest performance was obtained from all features analysis, v-SVM, RBF kernel, v = 0.23 outputs an accuracy of 90.909%, and the key features are Overweight and Technical - tactical abilities.

Publication Year
2018
Language
eng
Topic
MACHINE LEARNING
WRAPPER - EMBEDDED METHOD
PERFORMANCE
APRENDIZAJE AUTOMÁTICO
MÉTODOS WRAPPER - EMBEDDED
RENDIMIENTO
Repository
Repositorio Universidad de las Fuerzas Armadas
Get full text
http://repositorio.espe.edu.ec/handle/21000/15269
Rights
openAccess
License