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Titlebook: Unsupervised Learning Algorithms; M. Emre Celebi,Kemal Aydin Book 2016 Springer International Publishing Switzerland 2016 Big Data Pattern

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樓主: ACORN
31#
發(fā)表于 2025-3-27 00:01:00 | 只看該作者
Genetic Algorithms for Subset Selection in Model-Based Clustering,assumes no clustering for the same subset. Thus, the problem amounts to finding the feature subset which maximises such a criterion. A search over the potentially vast solution space is performed using genetic algorithms, which are stochastic search algorithms that use techniques and concepts inspir
32#
發(fā)表于 2025-3-27 04:23:42 | 只看該作者
Clustering Evaluation in High-Dimensional Data,ing quality indexes. We analyze the stability and discriminative power of a set of standard clustering quality measures with increasing data dimensionality. Our evaluation shows that the curse of dimensionality affects different clustering quality indexes in different ways and that some are to be pr
33#
發(fā)表于 2025-3-27 06:25:36 | 只看該作者
34#
發(fā)表于 2025-3-27 09:27:20 | 只看該作者
35#
發(fā)表于 2025-3-27 16:13:34 | 只看該作者
36#
發(fā)表于 2025-3-27 18:13:12 | 只看該作者
37#
發(fā)表于 2025-3-27 23:04:23 | 只看該作者
A Fuzzy-Soft Competitive Learning Approach for Grayscale Image Compression,ed methodology is rigorously compared to other relative approaches that exist in the literature. An interesting outcome of the simulation study is that although the proposed algorithm constitutes a fuzzy-based learning mechanism, it finally obtains computational costs that are comparable to crisp-ba
38#
發(fā)表于 2025-3-28 05:39:33 | 只看該作者
39#
發(fā)表于 2025-3-28 08:08:19 | 只看該作者
The Application of LSA to the Evaluation of Questionnaire Responses,natural language over time. The applications described in this chapter leverage LSA as an unsupervised system to learn language and provide a semantic framework that can be used for mapping natural language responses, evaluating the quality of those responses, and identifying relevant instructional
40#
發(fā)表于 2025-3-28 10:37:05 | 只看該作者
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