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Titlebook: New Frontiers in Applied Data Mining; PAKDD 2009 Internati Thanaruk Theeramunkong,Cholwich Nattee,Graham Will Conference proceedings 2010 S

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41#
發(fā)表于 2025-3-28 18:31:59 | 只看該作者
Irena Koprinskat University of Potsdam. In my opinion, it will undoubtedly also become a standard reference book on the desk of most scientists working with rocks, such as geophysicists, structural geologists, rock mechanics experts, as well as geotechnical and petroleum en- neers. That is because this book is con
42#
發(fā)表于 2025-3-28 19:50:52 | 只看該作者
43#
發(fā)表于 2025-3-29 01:15:51 | 只看該作者
44#
發(fā)表于 2025-3-29 06:09:49 | 只看該作者
Kobkrit Viriyayudhakorn,Thanaruk Theeramunkong,Cholwich Nattee,Thepchai Supnithi,Manabu Okumura cause of groin, hip, low back, and buttock pain but can lead to substantial loss of time from athletic participation. The diagnosis may be difficult to make and, therefore, requires a high index of suspicion due to the broad differential diagnosis. Plain radiographs are the first step in imaging ev
45#
發(fā)表于 2025-3-29 07:32:27 | 只看該作者
Vit Niennattrakul,Dechawut Wanichsan,Chotirat Ann Ratanamahatanaericson et al. Top Magn Reson Imaging 17:309–25, 2006; Brukner, Sports Med 26:415–24, 1998; Allen, Radiology 167:799–801, 1988), athletes who perform repetitive tasks with the shoulder and upper extremity may also develop stress fractures. Rib and shoulder girdle stress fractures account for less th
46#
發(fā)表于 2025-3-29 14:46:14 | 只看該作者
47#
發(fā)表于 2025-3-29 18:52:52 | 只看該作者
48#
發(fā)表于 2025-3-29 20:24:47 | 只看該作者
CODE: A Data Complexity Framework for Imbalanced Datasets,s the rare occurring events. Thus it is important to have a good performance on these classes while maintaining a reasonable overall accuracy. Although imbalanced datasets can be difficult to learn, but in the previous researches, the skewed class distribution has been suggested to not necessarily b
49#
發(fā)表于 2025-3-30 00:32:53 | 只看該作者
50#
發(fā)表于 2025-3-30 07:56:38 | 只看該作者
Undersampling Approach for Imbalanced Training Sets and Induction from Multi-label Text-Categorizatass. The most common approach is to address the problem of multi-label examples by inducing a separate binary classifier for each class, and then use these classifiers in parallel. What the information-retrieval community has all but ignored, however, is that such classifiers are almost always induc
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