By Boris Mirkin
Rather than the normal set of advert hoc concepts, Clustering for facts Mining: an information restoration strategy provides a thought that not just closes gaps in K-Means and Ward equipment, but in addition extends them into parts of present curiosity, resembling clustering combined scale info and incomplete clustering. the writer indicates unique tools for either cluster discovering and cluster description, addresses comparable subject matters akin to central part research, contingency measures, and information visualization, and comprises approximately 60 computational examples overlaying all levels of clustering, from facts pre-processing to cluster validation and effects interpretation.
This author's distinct recognition to facts restoration tools, theory-based suggestion, pre- and post-processing matters which are past the scope of so much texts, and transparent, useful directions for real-world info mining make this booklet perfect for nearly all reasons: for instructing, for self-study, and for pro reference.
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