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A Partitioned Fuzzy ARTMAP Implementation for Fast Processing of Large  (Make Corrections)  
Databases on Sequential Machines Jos e Castro and Michael Georgiopoulos and...



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Abstract: Fuzzy ARTMAP (FAM) is a neural network architecture that can establish the correct mapping between real valued input patterns and their correct labels. FAM can learn quickly compared to other neural network paradigms and has the advantage of incremental/online learning capabilities. Nevertheless FAM tends to slow down as the size of the data set grows. This problem is analyzed and a solution is proposed that can speed up the algorithm in sequential as well as parallel settings. (Update)

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BibTeX entry:   (Update)

@misc{ sequential-partitioned,
  author = "Databases On Sequential",
  title = "A Partitioned Fuzzy ARTMAP Implementation for Fast Processing of Large",
  url = "citeseer.ist.psu.edu/740466.html" }
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2177   Programs for Machine Learning (context) - SIGMOD, Quinlan - 1993
116   Fuzzy artmap: A neural network architecture for incremental .. (context) - Carpenter, Grossberg et al. - 1992
111   SLIQ: A fast scalable classifier for data mining - Mehta, Agrawal et al. - 1996
12   A monte carlo algorithm for fast projective clustering (context) - Procopiuc, Jones et al. - 2002

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