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Titlebook: Advances in Knowledge Discovery and Data Mining; 11th Pacific-Asia Co Zhi-Hua Zhou,Hang Li,Qiang Yang Conference proceedings 2007 Springer-

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樓主: 哪能仁慈
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發(fā)表于 2025-3-30 09:52:18 | 只看該作者
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發(fā)表于 2025-3-30 14:55:03 | 只看該作者
Overview of Hardware and Softwarerivacy/accuracy tradeoff by achieving perfect data mining accuracy. One apriori knowledge PCA based attack was recently investigated to show the vulnerabilities of this distance-preserving projected based perturbation approach when a sample dataset is available to attackers. As a result, non-distanc
53#
發(fā)表于 2025-3-30 20:27:40 | 只看該作者
Neuro-Ophthalmology Examination,d to evaluate the quality of a feature subset. The disadvantages of using dependency are discussed in this paper. And the problem of forward greedy search algorithm based on dependency is presented. We introduce the consistency measure to deal with the problems. The relationship between dependency a
54#
發(fā)表于 2025-3-30 22:39:25 | 只看該作者
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發(fā)表于 2025-3-31 02:05:25 | 只看該作者
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發(fā)表于 2025-3-31 07:43:02 | 只看該作者
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發(fā)表于 2025-3-31 11:22:29 | 只看該作者
G. Leclercq,S. Toma,J. C. Heusonhted graph adjacency matrix that contains all necessary information for clustering. The min-cut bipartitioning problem is a fundamental graph partitioning problem and is NP-Complete. In this paper, we present an effective multi-level algorithm based on ant colony optimization(ACO) for bisecting grap
58#
發(fā)表于 2025-3-31 13:25:05 | 只看該作者
A. Piffanelli,S. Fumero,D. Pelizzolaationship between these two issues, and presents a unifying method for dealing with both of them. Previous approaches often use parametric techniques and try to give exact results. In contrast, we present a nonparametric method based on local polynomial fitting, and give approximate results by fuzzy
59#
發(fā)表于 2025-3-31 19:41:31 | 只看該作者
60#
發(fā)表于 2025-3-31 23:29:55 | 只看該作者
The Importance of Being Siblings in a database. Though we can solve this kind of model selection problem with some statistical criteria such as the minimum description length (MDL) through implementing the EM algorithm, the process of evaluating these criteria may incur a large computational cost. From competitive learning perspec
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