Economical active feature-value acquisition through Expected Utility estimation

作者: Prem Melville , Foster Provost , Maytal Saar-Tsechansky , Raymond Mooney , None

DOI: 10.1145/1089827.1089828

关键词: Expected utility hypothesisTraining setMachine learningArtificial intelligenceEstimationComputer scienceValue (computer science)Feature (computer vision)Missing dataActive learning (machine learning)Data miningUnit cost

摘要: … However, when many inexpensive features are also uninformative, Cheapest-first performs worse than a random acquisition policy (Figure 2(b)). Sampled Expected Utility, however, …

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