[HTML][HTML] 不平衡数据分类方法综述
李艳霞， 柴毅， 胡友强， 尹宏鹏 - 控制与决策, 2019 - kzyjc.alljournals.cn
随着信息技术的快速发展, 各领域的数据正以前所未有的速度产生并被广泛收集和存储,
如何实现数据的智能化处理从而利用数据中蕴含的有价值信息已成为理论和应用的研究热点 …
如何实现数据的智能化处理从而利用数据中蕴含的有价值信息已成为理论和应用的研究热点 …
不平衡数据集分类方法研究综述.
周玉， 孙红玉， 房倩， 夏浩 - Application Research of …, 2022 - search.ebscohost.com
社会发展的同时带来大量数据的产生, 不平衡成为众多数据集的显著特点, 如何使不平衡数据集
得到更好的分类效果成为了机器学习的研究热点. 基于此, 对目前存在的不平衡数据集分类方法 …
得到更好的分类效果成为了机器学习的研究热点. 基于此, 对目前存在的不平衡数据集分类方法 …
A neural network learning algorithm for highly imbalanced data classification
The imbalanced data problem exists in many real-world datasets. Neural networks are one
popular method for classifying imbalanced data. However, data imbalance often negatively …
popular method for classifying imbalanced data. However, data imbalance often negatively …
Improving lazy decision tree for imbalanced classification by using skew-insensitive criteria
C Su, J Cao - Applied Intelligence, 2019 - Springer
Lazy decision tree (LazyDT) constructs a customized decision tree for each test instance,
which consists of only a single path from the root to a leaf node. LazyDT has two strengths in …
which consists of only a single path from the root to a leaf node. LazyDT has two strengths in …