内存约束下数据流分类的蒙德里安森林

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Martin Khannouz, Tristan Glatard
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引用次数: 0

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Mondrian forest for data stream classification under memory constraints

Mondrian forest for data stream classification under memory constraints
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来源期刊
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery 工程技术-计算机:人工智能
CiteScore
10.40
自引率
4.20%
发文量
68
审稿时长
10 months
期刊介绍: Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.
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