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Titlebook: Data Mining for Scientific and Engineering Applications; Robert L. Grossman,Chandrika Kamath,Raju R. Nambur Book 2001 Springer Science+Bus

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發(fā)表于 2025-3-28 17:01:14 | 只看該作者
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發(fā)表于 2025-3-29 00:32:36 | 只看該作者
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發(fā)表于 2025-3-29 06:40:28 | 只看該作者
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發(fā)表于 2025-3-29 09:00:06 | 只看該作者
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發(fā)表于 2025-3-29 14:54:55 | 只看該作者
Mining Residue Contacts in Proteins,leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.
47#
發(fā)表于 2025-3-29 15:57:03 | 只看該作者
On Mining Scientific Datasets, of data, a brief survey of the work presented at recent conferences in data mining and knowledge discovery might lead one to believe that these techniques are being applied mainly to commercial data sets, to address problems such as customer relationship management, market basket analysis, credit c
48#
發(fā)表于 2025-3-29 21:00:59 | 只看該作者
Understanding High Dimensional and Large Data Sets: Some Mathematical Challenges and Opportunities,nal sets arise naturally in a variety of contexts such as the dynamics of the Internet, imaging for surveillance and diagnostics, and gene sequencing. The significant change in the scale and complexity embodied in these types of data, as well as the intricacies of the underlying phenomena being stud
49#
發(fā)表于 2025-3-30 00:15:25 | 只看該作者
Data Mining at the Interface of Computer Science and Statistics,istical thinking in modern data mining. Data mining has attracted considerable attention both in the research and commercial arenas in recent years, involving the application of a variety of techniques from both computer science and statistics. The chapter discusses how computer scientists and stati
50#
發(fā)表于 2025-3-30 04:43:06 | 只看該作者
Mining Large Image Collections,ntinued improvements in acquisition and storage technology are yielding new image sets with data volumes measured in terabytes. Within these large image collections there is a wealth of scientific information, but getting from the data to knowledge is a difficult problem both due to the size of the
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