Capítulo de Libro
Empirical Evaluation of the Difficulty of Finding a Good Value of k for the Nearest Neighbor
Autor/es | Ferrer Troyano, Francisco Javier
Aguilar Ruiz, Jesús Salvador Riquelme Santos, José Cristóbal |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2003 |
Fecha de depósito | 2016-03-31 |
Publicado en |
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Resumen | As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute ... As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute values. Or at least, if there is a pattern for the parameter k in the original search space. We have carried out different approaches based onthe Nearest Neighbor technique and calculated the prediction accuracy for a group of databases from the UCI repository. Based on the experimental results of our study, we can state that, in general, it is not possible to know a priori a specific value of k to correctly classify an unseen example. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Empirical evaluation.pdf | 6.587Mb | [PDF] | Ver/ | |