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Embedding sample points uncertainty measures in learning algorithms
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DOI：10.1016/j.nahs.2006.12.004.png)
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Abstract
En 中文
Learning algorithms consider a sample consisting of pairs (pattern, label) and output a decision rule, possibly: (i) associating each pattern with the corresponding label, and (ii) generalizing to new patterns drawn from the same distribution of the original sample. This work proposes a set of methodologies to be applied to existing learning strategies in order to deal with more complex kinds of data sets, carrying also a quantitative measure on the quality of each label. (c) 2007 Elsevier Ltd. All rights reserved.
Keywords:
Uncertainty-measured samples
Learning
Data of variable quality
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4.1
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1.4K
Citations:
3.1K
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