Title
Empirical evaluation of the difficulty of finding a good value of k for the nearest neighbor
Date Issued
01 January 2003
Access level
open access
Resource Type
review
Author(s)
Ferrer-Troyano F.J.
Riquelme J.C.
Universidad de Sevilla
Publisher(s)
Springer Verlag
Abstract
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 parameter 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 on the 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. © Springer-Verlag Berlin Heidelberg 2003.
Start page
766
End page
773
Volume
2658
Language
English
OCDE Knowledge area
Ciencias de la computación Ingeniería de sistemas y comunicaciones
Scopus EID
2-s2.0-35248891181
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
Sources of information: Directorio de Producción Científica Scopus