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DGRLVQ
Dynamic Generalized Relevance Learning Vector Quantization
Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different... -
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My ZZZ Knowledge Micro Web Base
This is a base which stores knowledge in the form of nested sets
Hi, we are introducing you something new - ZZZ Knowledge Base. This is a base which stores knowledge in the form of nested sets, each set can contain a virtually unlimited number of elements and, in turn, each element can contain multiple elements. The access time from multiple ELEMENT NOT DEPEND ON THE NUMBER OF ITEMS IN IT AND PRACTICAL instantaneous! The access to knowledge base is realized through a "server" to which you can connect an unlimited number of "clients" as one computer...
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