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 ...

Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries.

Minimum discrimination information provides a useful generalization of likelihood methodology for classification and clustering of multivariate time series. Discrimination between different classes of ...