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- Title
AVOIDING NOISE AND OUTLIERS IN K-MEANS.
- Authors
Jnena, Rami; Timraz, Mohammed; Ashour, Wesam
- Abstract
Applying k-means algorithm on the datasets that include large number of noise and outlier objects, gives unclear clusters results. In this paper we proposed a new technique for avoiding these noise and outliers by applying some preprocessing and post processing steps for the dataset that have to be clustered by k-means. Our experimental results demonstrated that our scheme can avoid and eliminate the noise and outliers of the dataset in an efficient and accurate way.
- Publication
Computing & Information Systems, 2011, Vol 15, Issue 2, p1
- ISSN
1352-9404
- Publication type
Academic Journal