The UCI KDD archive of large data sets for data mining research and experimentation-Reference-Cited by-同舟云学术

The UCI KDD archive of large data sets for data mining research and experimentation

Published:2000-12 Issue:2 Volume:2 Page:81-85
ISSN:1931-0145
Container-title:ACM SIGKDD Explorations Newsletter
language:en
Short-container-title:SIGKDD Explor. Newsl.

Author:

Bay Stephen D.¹,Kibler Dennis¹,Pazzani Michael J.¹,Smyth Padhraic¹

Affiliation:

1. Department of Information and Computer Science, University of California, Irvine, Irvine, CA

Publisher

Association for Computing Machinery (ACM)

Reference8 articles.

1. {1} C. Blake and C. J. Merz. UCI repository of machine learning databases. Irvine CA: University of California Department of Information and Computer Science. {http://www.ics.uci.edu/~mlearn/MLRepository.html}. 1998. {1} C. Blake and C. J. Merz. UCI repository of machine learning databases. Irvine CA: University of California Department of Information and Computer Science. {http://www.ics.uci.edu/~mlearn/MLRepository.html}. 1998.

2. A Multiple Model Cost-Sensitive Approach for Intrusion Detection

3. Digital libraries and autonomous citation indexing

Cited by 102 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. Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets;Expert Systems with Applications;2024-03

2. An ensemble framework with improved hybrid breeding optimization-based feature selection for intrusion detection;Future Generation Computer Systems;2024-02

3. Designing accurate lightweight intrusion detection systems for IoT networks using fine-tuned linear SVM and feature selectors;Computers & Security;2024-02

4. Sanitized clustering against confounding bias;Machine Learning;2023-12-27

5. Deep Reinforcement Learning for intrusion detection in Internet of Things: Best practices, lessons learnt, and open challenges;Computer Networks;2023-11