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25 May 2023 Cluster and denoise data with general ratio density
Junliang Wu, Ziniu Yu, William Zhu
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Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126360M (2023) https://doi.org/10.1117/12.2675242
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China
Abstract
Density-based clustering is famous for its ability to extract clusters of arbitrary shapes and to detect noise samples, but many existing density-based clustering algorithms suffer from high dimensional or varying density data. To address these issues, we introduce a novel density-based clustering algorithm, general ratio density (GRD). Based on k-NN graph, it combines global density estimation and local density estimation to better detect noise points in varying density situations. During the process of shifting noise points and dividing clusters, our clustering algorithm can cluster and denoise at the same time. Experiment results on real life dataset and synthetic dataset demonstrates the state-of-the-art performance of our algorithm compared to other methods.
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Junliang Wu, Ziniu Yu, and William Zhu "Cluster and denoise data with general ratio density", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126360M (25 May 2023); https://doi.org/10.1117/12.2675242
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KEYWORDS
Machine learning
Artificial intelligence
Data mining
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