Mining Uncertain Data Streams Using Clustering Feature Decision Trees

Author:

Xu Wenhua,Qin Zheng,Hu Hao,Zhao Nan

Publisher

Springer Berlin Heidelberg

Reference26 articles.

1. Aggarwal, C.C., Han, J., Wang, J., Yu, P.: A Framework for Clustering Uncertain Data Streams. In: Proc. 24th Int. Conf. on Data Engineering, pp. 150–159 (2008)

2. Aggarwal, C.C.: Managing and Mining Uncertain Data. Springer Publishing Company, Incorporated (2009)

3. Bi, J., Zhang, T.: Support Vector Classification with Input Data Uncertainty. In: NIPS 2004: Advances in Neural Information Processing Systems, vol. 16, pp. 161–168 (2004)

4. Bifet, A., Kirkby, R., Holmes, G., Pfahringer, B.: MOA: Massive Online Analysis (2007), http://sourceforge.net/projects/moa-datastream

5. Bifet, A., Holmes, G., Pfahringer, B., Kirkby, R., Gavalda, R.: New ensemble methods for evolving data streams. In: Proc. 15th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, pp. 139–148 (2009)

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1. Clustering Data Stream with Rough Set;Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition;2019-10-23

2. Correcting the Usage of the Hoeffding Inequality in Stream Mining;Advances in Intelligent Data Analysis XII;2013

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