Dynamic Correlation-Based Feature Selection for Feature Drifts in Data Streams
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/8910170/8923611/08923975.pdf?arnumber=8923975
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Adaptive threshold optimisation for online feature selection using dynamic particle swarm optimisation in determining feature relevancy and redundancy;Applied Soft Computing;2024-05
2. An Adaptive Streaming Feature Selection Technique for Classifying Non-Stationary Data Streams;2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT);2023-10-26
3. A dynamic feature selection and intelligent model serving for hybrid batch-stream processing;Knowledge-Based Systems;2022-11
4. Assessing Batch and Online Learning for Delivery in Full and On Time Predictions;2022 International Joint Conference on Neural Networks (IJCNN);2022-07-18
5. Online Feature Screening for Data Streams with Concept Drift;IEEE Transactions on Knowledge and Data Engineering;2022
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