An Adaptive Voting Mechanism Based on Relative Density for Filtering Label Noises-Reference-Cited by-同舟云学术

An Adaptive Voting Mechanism Based on Relative Density for Filtering Label Noises

Published:2022-05-13 Issue: Volume: Page:
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Container-title:2022 IEEE 5th International Conference on Electronics Technology (ICET)
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Author:

Huang Longhai¹,Shao Yabin¹,Peng Jialin¹

Affiliation:

1. Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Computational Intelligence, College of Computer Science and Technology,Chongqing,China

Funder

Research and Development

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9823394/9823964/09824605.pdf?arnumber=9824605

Reference23 articles.

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2. Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach

3. Fast rates for a knn classifier robust to unknown asymmetric label noise;reeve;International Conference on Machine Learning,2019

4. Estimating a kernel fisher discriminant in the presence of label noise[C];lawrence;18th International Conference on Machine Learning (ICML 2001) Morgan Kaufmann,2001

5. Support vector machines under adversarial label noise[C];biggio;Asian Conference on Machine Learning,2011

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