EM in High-Dimensional Spaces
نویسندگان
چکیده
منابع مشابه
On high dimensional data spaces
Data mining applications usually encounter high dimensional data spaces. Most of these dimensions contain ‘uninteresting’ data, which would not only be of little value in terms of discovery of any rules or patterns, but have been shown to mislead some classification algorithms. Since, the computational effort increases very significantly (usually exponentially) in the presence of a large number...
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We show that, under certain assumptions, the fitness of almost all quasi-species becomes independent of mutational probabilities and the initial frequency distributions of the sequences in high dimensional sequence spaces. This result is the consequence of the concentration of measure on a high dimensional hypersphere and its extension to Lipschitz functions knows as the Levy’s Lemma. Therefore...
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Many spatial access methods, such as the R-tree, have been designed to support spatial search operators (e.g., overlap, containment, and enclosure) over both points and regional objects in multi-dimensional spaces. Unfortunately, contemporary spatial access methods are limited by many problems that significantly degrade the query performance in high-dimensional spaces. This chapter reviews the ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)
سال: 2005
ISSN: 1083-4419
DOI: 10.1109/tsmcb.2005.846670