000125190 001__ 125190 000125190 005__ 20230322092655.0 000125190 037__ $$aTAZ-TFG-2022-2912 000125190 041__ $$aeng 000125190 1001_ $$aIzcue Domínguez, Nerea 000125190 24200 $$aUnsupervised Learning. Applications in biomechanics 000125190 24500 $$aAprendizaje no supervisado. Aplicaciones en biomecánica 000125190 260__ $$aZaragoza$$bUniversidad de Zaragoza$$c2022 000125190 506__ $$aby-nc-sa$$bCreative Commons$$c3.0$$uhttp://creativecommons.org/licenses/by-nc-sa/3.0/ 000125190 520__ $$aThis end of degree project will be focus in two main Unsupervised Learning techniques: Principal Component Analysis and Clustering. Principal Component Analysis is presented in the first chapter and Clustering in the second, focusing in three of the most used algorithms: K-means, K-medoids and Hierarchical Clustering. In the third chapter, a biomechanical example based on a real data set is presented in order to illustrate the application of these two techniques.<br /><br /> 000125190 521__ $$aGraduado en Matemáticas 000125190 540__ $$aDerechos regulados por licencia Creative Commons 000125190 700__ $$aLafuente Blasco, Miguel$$edir. 000125190 700__ $$aSanz Sáiz, Gerardo$$edir. 000125190 7102_ $$aUniversidad de Zaragoza$$bMétodos Estadísticos$$cEstadística e Investigación Operativa 000125190 8560_ $$f764160@unizar.es 000125190 8564_ $$s1728909$$uhttps://zaguan.unizar.es/record/125190/files/TAZ-TFG-2022-2912.pdf$$yMemoria (eng) 000125190 909CO $$ooai:zaguan.unizar.es:125190$$pdriver$$ptrabajos-fin-grado 000125190 950__ $$a 000125190 951__ $$adeposita:2023-03-21 000125190 980__ $$aTAZ$$bTFG$$cCIEN 000125190 999__ $$a20220627122835.CREATION_DATE