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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Veröffentlicht in:	Machine learning. 54, 2 (2004).
1. Verfasser:	Saar-Tsechansky, Maytal
Format:	Artikel
Sprache:	English
Schlagworte:	Active learning. Cost-sensitive learning. Class probability estimation. Ranking. Supervised learning. Decision trees. Uncertainty sampling. Selective sampling.