A new family of mixture models for the model-based clustering of longitudinal data is introduced.
The covariance structures of eight members of this new family of models are given and the associated maximum likelihood ...
In recent years, work has been carried out on clustering gene expression microarray data. Some approaches are developed from an algorithmic viewpoint whereas others are developed via the application of mixture models. In ...
A clustering algorithm which is based on density and adaptive density-reachable is developed and presented for arbitrary data point distributions in some real world applications, especially in geophysical data interpretation. ...
This paper discusses the theory and algorithmic design of the CADD (clustering algorithm based on object density and direction) algorithm. This algorithm seeks to harness the respective advantages of the k-means and DENCLUE ...