Unsupervised K-Means Clustering Algorithm

The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the k-means algorithm and its extensions are always influenced by initializations with a necessary number of clusters a priori. That is, the k-means algorithm is not exactly an unsupervised clustering method. In this paper, we construct an unsupervised learning schema for the k-means algorithm so that it is free of initializations without parameter selection and can also simultaneously find an optimal number of clusters. That is, we propose a novel unsupervised…

• MO
  Ministry of Science and Technology, Taiwan

  Awards: MOST 107, MOST 107-, MOST 107-2118-M-033-002-MY2, 107-2118-M-033-002-MY2