Clustering and classification represent the opportunity to apply categorical reasoning to vast data contexts we would otherwise find overwhelming.

Multi-target regression and predictive clustering techniques constitute a rapidly evolving area within the field of machine learning. In multi-target regression, models are designed to predict a ...

Instead, here is an explanation of clustering and classifying things the old-fashioned way: in an Excel spreadsheet. How classification works ...

The study of clustering and classification of uncertain data addresses the challenges posed by imprecise, noisy, or inherently probabilistic measurements common in many modern data acquisition systems ...

The class of stick-breaking priors and their extensions are considered in classification and clustering problems in which the complexity, the number of possible models or clusters, can be either ...

The issues of model-based clustering and classification of longitudinal data have received increasing attention in recent years. In this paper, we propose a finite mixture of multivariate t linear ...