Percolation and multimodal data structuring
In this article the problem of multimodal data analysis is considered in the framework of the percolation method. A new presentation is given and we summarize our experience. It must be recalled that it is the only method in data analysis to permit a classification of points into four categories: group points, boundary points, multimodal points and isolated points. These concepts allow to correctly describe the shape of any empirical density functions. Points related to same modes are ’group points’. The others permit to describe the relative position of groups with respect to themselves. So the method appears to be a hybrid one between clustering analysis and pattern recognition. Comparisons with other data analysis methods are given.
KeywordsBoundary Point Group Point Support Point Dissimilarity Matrix Perception Level
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