Delegating Classifiers
- Topics:
- Delegation
- Tags:
- Author,
- University Of Bristol
- Source:
- University of Bristol
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Overview: A sensible use of classifiers must be based on the estimated reliability of their predictions. A cautious classifier would delegate the difficult or uncertain predictions to other, possibly more specialised, classifiers. In this paper the author's analyse and develop this idea of delegating classifiers in a systematic way. First, the author design a two-step scenario where a first classifier chooses which examples to classify and delegates the difficult examples to train a second classifier. Secondly, the author presents an iterated scenario involving an arbitrary number of chained classifiers.
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Format: PDF | Size: 955KB | Date: Apr 2004 | Pages: 8
