Combining Feature Selection with Feature Weighting for k-NN Classifier

Author:

Bao Yongguang,Du Xiaoyong,Ishii Naohiro

Publisher

Springer Berlin Heidelberg

Reference16 articles.

1. D.W. Aha, D. Kibler & M.K. Albert, “Instance-Based Learning Algorithms”, Machine Learning, Vol. 6, 1991,pp. 37–66.

2. D.W. Aha, “Tolerating Noisy, Irrelevant and Novel Attributes in Instance-Based Learning Algorithm”, International Journal of Man-Machine Studies, Vol. 36, No. 1, 1992, pp. 267–287.

3. D.W. Aha & R.L. Bankert, “Feature Selection for Case-Based Classification of Cloud Types: An Empirical Comparison”, In D.W. Aha (Ed.) Case-Based Reasoning: Papers from the 1994 Worksho ((TR WS-94-10), Menlo Park, CA: AAAI press.

4. D.W. Aha, “Feature Weighting for Lazy Learning Algorithms”, In H. Liu & H. Motoda (Eds.) Feature Extraction, Construction and Selection: A Data Mining Perspective, Norwell MA: Kluwer, 1998.

5. N.F. Ayan, “Using Information Gain as Feature Weight”, 8th Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN’99), Istanbul, Turkey, June 1999.

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