关键词: 监督椭球聚类学习, 最近邻分类器, 多类

Abstract: This paper proposes a locally adaptive nearest neighbor classification method based on supervised learning style which works well for the classes more than two. In this method, the ellipsoid clustering learning method is applied to estimate an effective metric for producing neighborhood that is elongated along less discriminating feature dimensions and constricted along most discriminating ones. As a result, the class conditional probabilities can be expected to be approximately constant in the modified neighborhoods, whereby better classification performance can be achieved. The experimental results show that this is an efficient and robust classification method for multi-class problems.

Key words: supervised ellipsoid clustering, nearest neighbor classifiers, multi-class