Selective Sampling Using the Query by Committee Algorithm

We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain with positive lower bound, then the prediction error decreases exponentially with the numbe...

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Bibliographic Details
Published in:Machine learning 1997-08, Vol.28 (2-3), p.133
Main Authors: Freund, Yoav, Seung, H Sebastian, Shamir, Eli, Tishby, Naftali
Format: Article
Language:English
Subjects:
Studies
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Summary:We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain with positive lower bound, then the prediction error decreases exponentially with the number of queries. We show that, in particular, this exponential decrease holds for query learning of perceptrons.[PUBLICATION ABSTRACT]
ISSN:0885-6125
1573-0565
DOI:10.1023/A:1007330508534