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Titlebook: Advances in Self-Organizing Maps; 7th International Wo José C. Príncipe,Risto Miikkulainen Conference proceedings 2009 Springer-Verlag Berl

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楼主: Hallucination
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On the Quantization Error in SOM vs. VQ: A Critical and Systematic Study,ctors using a finite set of models. In both methods, the quantization error (QE) of an input vector can be expressed, e.g., as the Euclidean norm of the difference of the input vector and the best-matching model. Since the models are usually optimized in the VQ so that the sum of the squared QEs is
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Career-Path Analysis Using Optimal Matching and Self-Organizing Maps,ors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important
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Network-Structured Particle Swarm Optimizer with Various Topology and Its Behaviors,topology as rectangular, hexagonal, cylinder and toroidal. We apply NS-PSO with various topology to optimization problems. We investigate their behaviors and evaluate what kind of topology would be the most appropriate for each function.
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Computational Stochastic Programmingsual AP. To evaluate the performance of FAP we compare the clustering results of FAP for different experimental and real world problems with solutions obtained by employing Median Fuzzy c-Means (M-FCM) and Fuzzy c-Means (FCM). As measure for cluster agreements we use a fuzzy extension of Cohen’s . based on t-norms.
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