Radius Knn Classifier Using Aggregation Of Fuzzy Equivalences

The paper presents a modified classification method based on the k-nearest neighbor algorithm. In the modified k-NN algorithm some aggregations of fuzzy equivalences are used instead of metrics and the selection of the nearest neighbors is limited by their closeness from a tested object. This procedure is intended to improve suitability of the k-NN algorithm, when a significant part of the closest neighbors is not close enough to the tested object. Additionally, some theoretical results concerning fuzzy equivalences and their aggregations are included in the paper.