A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering

Density-based clustering is able to find clusters of arbitrary sizes and shapes while effectively separating noise. Despite its advantage over other types of clustering, it is well-known that most density-based algorithms face the same challenge ...

Partitional clustering is an important part of cluster analysis. Based on various theories, numerous clustering algorithms have been developed, and new clustering algorithms continue to appear in the literature. It is known that Occam's razor plays a ...

Support Vector Machine Clustering (SVMC) is a model-based clustering method designed primarily for solving 2-class clustering problems. In this paper, we generalize the SVMC method to multi-class clustering via two different strategies, namely One-...