2006 AnytimeClassificationUsingtheNe

• (Ueno et al., 2006) ⇒ Ken Ueno, Xiaopeng Xi, Eamonn Keogh, and Dah-Jye Lee. (2006). “Anytime Classification Using the Nearest Neighbor Algorithm with Applications to Stream Mining.” In: Proceedings of the Sixth International Conference on Data Mining. doi:10.1109/ICDM.2006.21

Subject Headings: Anytime Algorithm, Stream Mining.

Cited By

• http://scholar.google.com/scholar?q=%22Anytime+Classification+Using+the+Nearest+Neighbor+Algorithm+with+Applications+to+Stream+Mining%22+2006
• http://dl.acm.org/citation.cfm?id=1193207.1193365&preflayout=flat#citedby

Quotes

Abstract

For many real world problems we must perform classification under widely varying amounts of computational resources. For example, if asked to classify an instance taken from a bursty stream, we may have from milliseconds to minutes to return a class prediction. For such problems an anytime algorithm may be especially useful. In this work we show how we can convert the ubiquitous nearest neighbor classifier into an anytime algorithm that can produce an instant classification, or if given the luxury of additional time, can utilize the extra time to increase classification accuracy. We demonstrate the utility of our approach with a comprehensive set of experiments on data from diverse domains.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2006 AnytimeClassificationUsingtheNe	Eamonn Keogh Ken Ueno Xiaopeng Xi Dah-Jye Lee			Anytime Classification Using the Nearest Neighbor Algorithm with Applications to Stream Mining				10.1109/ICDM.2006.21