The identification and recognition of temporal rainfall patterns is important useful not only for climatological studies, but mainly supporting rainfall–runoff modeling water resources management. Clustering techniques applied to data provide meaningful ways producing concise inclusive pattern classifications. In this paper, a timeseries coming from the Greek National Bank Hydrological Meteorol...

Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed i...

Clustering is an important data mining technique which has gained a tremendous importance in recent times due to its inherent nature of capturing the hidden structure of the data. In Clustering, different objects that have some similarity based on their characteristics are brought together into a group. Hierarchical Clustering Analysis is one of the clustering techniques which play a significan...