Aprendizaje no supervisado. Aplicaciones en biomecánica

Izcue Domínguez, Nerea
Lafuente Blasco, Miguel (dir.) ; Sanz Sáiz, Gerardo (dir.)

Universidad de Zaragoza, CIEN, 2022
Métodos Estadísticos department, Estadística e Investigación Operativa area

Graduado en Matemáticas

Abstract: This end of degree project will be focus in two main Unsupervised Learning techniques: Principal Component Analysis and Clustering. Principal Component Analysis is presented in the first chapter and Clustering in the second, focusing in three of the most used algorithms: K-means, K-medoids and Hierarchical Clustering. In the third chapter, a biomechanical example based on a real data set is presented in order to illustrate the application of these two techniques.

Tipo de Trabajo Académico: Trabajo Fin de Grado