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31#
發(fā)表于 2025-3-26 21:34:12 | 只看該作者
A Survey of Clustering Data Mining Techniques,ys an important role in a broad range of applications. The applications of clustering usually deal with large datasets and data with many attributes. Exploration of such data is a subject of data mining. This survey concentrates on clustering algorithms from a data mining perspective.
32#
發(fā)表于 2025-3-27 01:20:53 | 只看該作者
S. Aronoff,J. Dainty,C. A. Swansonys an important role in a broad range of applications. The applications of clustering usually deal with large datasets and data with many attributes. Exploration of such data is a subject of data mining. This survey concentrates on clustering algorithms from a data mining perspective.
33#
發(fā)表于 2025-3-27 06:22:04 | 只看該作者
Mobile Forensics for iOS and Android Platforms: Chrome App Artifacts Depending on SQLite,nt and utilize mobile forensics methodology to analyze SQLite files from the applications that install on the mobile device, we discuss some of the techniques and tools used to extract information, and we present a case study of Chrome application. In terms of forensic analysis, the chapter will als
34#
發(fā)表于 2025-3-27 13:31:53 | 只看該作者
35#
發(fā)表于 2025-3-27 14:34:13 | 只看該作者
2524-728X ecentralisation, multilevel governance and local government This book sheds light on the central complexities of municipal cooperation and examines the dynamics, experiences and drivers of inter-municipal cooperation (IMC) in Europe. Particular attention is given to the features of governance arrang
36#
發(fā)表于 2025-3-27 20:07:57 | 只看該作者
37#
發(fā)表于 2025-3-28 01:38:13 | 只看該作者
38#
發(fā)表于 2025-3-28 04:02:24 | 只看該作者
2190-3018 ngs (IoT), machine learning, speech processing, sustainable high-performance systems, VLSI and embedded systems, image and video processing, and signal processing and communication..978-981-19-0013-6978-981-19-0011-2Series ISSN 2190-3018 Series E-ISSN 2190-3026
39#
發(fā)表于 2025-3-28 08:09:16 | 只看該作者
40#
發(fā)表于 2025-3-28 14:17:12 | 只看該作者
Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability forrity. The first method includes the Cox model, ensembled with the survival random forest. The second employs a survival tree algorithm to cluster the data, and then fits a separate Cox model in each cluster. The third uses the clusters obtained with a survival tree to identify interaction and non-li
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