教唆 发表于 2025-3-28 14:38:18

2524-552X e and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase su978-981-15-6697-4978-981-15-6695-0Series ISSN 2524-552X Series E-ISSN 2524-5538

啤酒 发表于 2025-3-28 20:40:46

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Nmda-Receptor 发表于 2025-3-29 01:59:51

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为敌 发表于 2025-3-29 07:03:48

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maladorit 发表于 2025-3-29 09:32:19

Lightweight Classifier-Based Outlier Detection Algorithms from Multivariate Data Stream, or lightweight analysis with sliding window, other than global analysis only.” These three mechanisms are then combined with the existing outlier measurements such as “interquartile, local outlier factor and Mahalanobis distance range.” In this study, the computer simulation experiments show encour

Fillet,Filet 发表于 2025-3-29 12:52:05

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subordinate 发表于 2025-3-29 18:44:19

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忘川河 发表于 2025-3-29 20:40:40

Parameter Tuning onto Recurrent Neural Network and Long Short-Term Memory (RNN-LSTM) Network for Feave little value on output feature set. Deep learning methods have been applied to select relevant features in the classification problem; however, the current approach (i.e., search strategies) to the learning of a parameter can either grow out of bound or shrink (they decay exponentially in the nu

angiography 发表于 2025-3-30 01:19:47

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查看完整版本: Titlebook: Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing; Simon James Fong,Richard C. Millham