- Mazón J.N., Micó L., Moreno-Seco F.
"New neighborhood based classification rules for metric spaces and their use in ensemble classification"
Lecture Notes in Computer Science, vol. 4477, pp. 354-361
The k-nearest-neighbor rule is a well known pattern recognition technique with very good results in a great variety of real classification
tasks. Based on the neighborhood concept, several
classification rules have been proposed to reduce the error rate of the k-nearest-neighbor rule (or its time requirements). In this work, two new geometrical neighborhoods are defined and the classification rules derived from them are used in several real data classification tasks. Also, some voting ensembles of classifiers based on these
new rules have been tested and compared.
author = "Mazón J.N., Micó L., Moreno-Seco F.",
title = "New neighborhood based classification rules for metric spaces and their use in ensemble classification",
journal = "Lecture Notes in Computer Science",
number = "to appear",
pages = "354-361",
volume = "4477",
year = "2007"