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A simple extension of boosting for asymmetric mislabeled data
Kenichi Hayashi
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Article
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peer-review
3
Citations (Scopus)
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Dive into the research topics of 'A simple extension of boosting for asymmetric mislabeled data'. Together they form a unique fingerprint.
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Mathematics
Boosting
100%
Binary Data
21%
Loss Function
19%
Likelihood
16%
Numerical Experiment
13%
Interpretation
13%
Cost-sensitive Learning
2%
Business & Economics
Boosting
77%
Loss Function
20%
Numerical Experiment
19%
Costs
7%