This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.
表中的内容
The Context.- Origins in Context.- Relevant Literature Review.- Theory and Algorithms.- Novel Mathematical Background.- Real-World Grounding.- Knowledge Representation.- The Modeling Problem and its Formulation.- Algorithms for Clustering, Classification, and Regression.- Applications and Comparisons.- Numeric Data Applications.- Nonnumeric Data Applications.- Connections with Established Paradigms.- Conclusion.- Implementation Issues.- Discussion.
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