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Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms

Discovery Science, no. 2 (2002): 131-152

Cited: 105|Views43
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Abstract

Scalability is a key requirement for any KDD and data mining algorithm, and one of the biggest research challenges is to develop methods that allow to use large amounts of data. One possible approach for dealing with huge amounts of data is to take a random sample and do data mining on it, since for many data mining applications approxima...More

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