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Active Sampling for Class Probability Estimation and Ranking.

In many cost-sensitive environments class probability estimates are used by decision makers to evaluate the expected utility from a set of alternatives. Supervised learning can be used to build class probability estimates; however, it often is very costly to obtain training data with class labels. A...

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Bibliografische gegevens
Gepubliceerd in:Machine learning. 54, 2 (2004).
Hoofdauteur: Saar-Tsechansky, Maytal
Formaat: Artikel
Taal:Engels
Onderwerpen:
Active learning.
Cost-sensitive learning.
Class probability estimation.
Ranking.
Supervised learning.
Decision trees.
Uncertainty sampling.
Selective sampling.