Knowledge Discovery from Noisy Datasets
Author:
Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-642-25646-2_72.pdf
Reference22 articles.
1. Khoshgoftaar, T.M., Seliya, N.: The necessity of assuring quality in software measurement data. In: Pro. of 10th International Software Metrics Symposium, pp. 119–130 (2004)
2. Weiss, G.M.: Mining with rarity: a unifying framework. SIGKDD Explorations 6(1), 7–19 (2004)
3. Zhu, X., Wu, X.: Class noise vs. attribute noise: a quantitative study of their impacts. Artificial Intelligence Review 22(3-4), 177–210 (2004)
4. Brodley, C.E., Friedl, M.A.: Identifying mislabeled training data. Journal of Artificial Intelligence Research 11, 131–167 (1999)
5. Khoshgoftaar, T.M., Zhong, S., Joshi, V.: Enhancing software quality estimation using ensemble-classifier based noise filtering. Intelligent Data Analysis: An International Journal 9(1), 3–27 (2005)
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