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Titlebook: Advances in Artificial Intelligence; 30th Canadian Confer Malek Mouhoub,Philippe Langlais Conference proceedings 2017 Springer Internationa

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樓主: Dopamine
41#
發(fā)表于 2025-3-28 17:09:31 | 只看該作者
Conference proceedings 2017ada, in May 2017. The 19 regular papers and 24 short papers presented together with 6 Graduate Student Symposium papers were carefully reviewed and selected from 62 submissions. The focus of the conference was on the following subjects: Data Mining and Machine Learning; Planning and Combinatorial Op
42#
發(fā)表于 2025-3-28 21:06:48 | 只看該作者
0302-9743 ing subjects: Data Mining and Machine Learning; Planning and Combinatorial Optimization; AI Applications; Natural Language Processing; Uncertainty and Preference Reasoning; and Agent Systems..978-3-319-57350-2978-3-319-57351-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
43#
發(fā)表于 2025-3-28 23:14:17 | 只看該作者
Anticancer Potential of Brassinosteroids,tly. To overcome this issue, we propose a deep neural network model to predict molecular subtypes of breast cancer using somatic CNAs. Experiments show that our deep model works much better than traditional SVM and RF.
44#
發(fā)表于 2025-3-29 05:52:48 | 只看該作者
https://doi.org/10.1007/BFb0077328r equivalence can be used to validate assumptions of co-similarity, which are required but often untested in co-clustering analyses. The method is robust to noise and asymmetric data, making it particularly suited for cluster analysis and recommendation in data of unknown structure. (An extended preprint of this paper is available at ..)
45#
發(fā)表于 2025-3-29 07:50:54 | 只看該作者
Asher Auel,Brendan Hassett,Bianca Virayg to be more effective in addressing the issue of highly imbalanced auction fraud datasets. We deploy a set of well-known binary classifiers to understand how the class imbalance affects the classification results. We choose the most relevant performance metrics to deal with both imbalanced data and fraud bidding data.
46#
發(fā)表于 2025-3-29 13:11:40 | 只看該作者
47#
發(fā)表于 2025-3-29 17:54:16 | 只看該作者
48#
發(fā)表于 2025-3-29 20:54:17 | 只看該作者
49#
發(fā)表于 2025-3-30 02:50:57 | 只看該作者
50#
發(fā)表于 2025-3-30 06:53:57 | 只看該作者
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