A Density Based Approach to Classification.
Hui Wang, David Bell, Ivo Düntsch · 2003
This paper presents a novel method for classification, which is density based and makes use of the models built by the lattice machine (LM) [5, 7]. Density is a natural concept to use in clustering and the LM is a relatively new method for supervised learning developed in recent years. The LM approximates data resulting in, as a model of data, a set of hyper tuples that are equilabelled, supported and maximal. The method presented in this paper uses the LM model of data to classify new data with a view to maximising the density of the model. In order for the method to have wide applicability a measure of density is introduced for hyper tuples and relations.