Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
Hierarchical categorization of documents is a task receiving growing interest due to the widespread proliferation of topic hierarchies for text documents. The worst problem of hie...
: Analysis-oriented database applications, such as data warehousing or customer relationship management, play a crucial role in the database area. In general, the multidimensional ...
Roland Pieringer, Klaus Elhardt, Frank Ramsak, Vol...
Abstract. This paper proposes a general approach named ExpectationMiniMax (EMM) for clustering analysis without knowing the cluster number. It describes the contrast function of Ex...