If there are more clusters than the ideal, each intrinsic cluster will be split into several subsets. Theoretically, this split can be arbitrary and neighboring data points have a ...
In this paper we propose the use of fractals and especially the Hilbert curve, in order to design good distance-preserving mappings. Such mappings improve the performance of secon...
In this paper, we propose a novel formulation for distance-based outliers that is based on the distance of a point from its kth nearest neighbor. We rank each point on the basis o...
In this paper we describe the parallelization of two nearest neighbour classification algorithms. Nearest neighbour methods are well-known machine learning techniques. They have be...
This paper proposes a novel nonparametric clustering algorithm capable of identifying shape-free clusters. This algorithm is based on a nonparametric estimation of the normalized ...
Chaolin Zhang, Xuegong Zhang, Michael Q. Zhang, Ya...