Incremental Supervised Classification for the MTE Distribution: a Preliminary Study

In this paper we propose an incremental method for building classifiers in domains with very large amounts of data or for data streams. The method is based on the use of mixtures of truncated exponentials, so that continuous and discrete variables can be handled simultaneously.

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