By Ali A. Ghorbani, Iosif-Viorel Onut (auth.), Manuel Graña Romay, Emilio Corchado, M. Teresa Garcia Sebastian (eds.)
th The five foreign convention on Hybrid man made Intelligence platforms (HAIS 2010) has turn into a different, validated and extensive interdisciplinary discussion board for researchers and practitioners who're keen on constructing and utilising symbolic and sub-symbolic strategies aimed toward the development of hugely strong and trustworthy problem-solving recommendations, and bringing the main appropriate achievements during this box. Overcoming the inflexible encasing imposed through the coming up orthodoxy within the box of arti- cial intelligence, which has ended in the partition of researchers into so-called components or fields, curiosity in hybrid clever platforms is transforming into simply because they offer freedom to layout cutting edge recommendations to the ever-increasing complexities of real-world pr- lems. Noise and uncertainty demand probabilistic (often Bayesian) equipment, whereas the massive volume of information at times asks for speedy heuristic (in the feel of suboptimal and ad-hoc) algorithms capable of provide solutions in applicable time frames. excessive dim- sionality calls for linear and non-linear dimensionality relief and have extr- tion algorithms, whereas the imprecision and vagueness demand fuzzy reasoning and linguistic variable formalization. not anything impedes real-life difficulties to combine diffic- ties, providing large amounts of noisy, imprecise and high-dimensional facts; consequently, the layout of ideas has to be in a position to inn to any software of the exchange to assault the matter. Combining different paradigms poses difficult difficulties of computational and methodological interfacing of a number of formerly incompatible techniques. this can be, hence, the environment of HAIS convention sequence, and its expanding luck is the facts of the power of this fascinating field.
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Additional resources for Hybrid Artificial Intelligence Systems: 5th International Conference, HAIS 2010, San Sebastián, Spain, June 23-25, 2010. Proceedings, Part I
G. Kaburlasos, A. E. Papadakis Order Metrics for Semantic Knowledge Systems . . . . . . . . . . . Cliﬀ Joslyn and Emilie Hogan 367 375 383 391 399 Granular Fuzzy Inference System (FIS) Design by Lattice Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . Vassilis G. Kaburlasos 410 Median Hetero-Associative Memories Applied to the Categorization of True-Color Patterns . . . . . . . . . . . . . .
In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 2(1), pp. 281–297 (1967) 18. : On the generalized distance in statistics. Proceedings of the National Instute of Science (India) 2(1), 49–55 19. html 20. : X-means: Extending k-means with eﬃcient estimation of the number of clusters. In: Proceedings of the Seventeenth International Conference on Machine Learning, pp. 727–734. Morgan Kaufmann, San Francisco (2000) 21. : Intrusion detection with unlabeled data using clustering.
Thus, diﬀerent selections of the initial centroids often lead to diﬀerent clustering results. This is mainly because K-means is based on the mean squared error and converges to a local minima . This can be easily seen if the initial centroids are not well separated. The second shortcoming of K-means is the dependency on the number of initial centroids, k. This requirement is hard to meet when the distribution of data is unknown, since obtaining an optimal initial k is an NP-hard problem .