Active Feature-Value Acquisition

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Strongly agree or strongly disagree?: Rating features in Support Vector Machines (2016, methodology): “2008, Turney 1995), obtaining feature information from the classi er (Saar-Tsechansky et al. 2009), or refreshing the classi er to include new data (Fang et al.”
Active Learning Literature Survey (2009, background): “, 2004), or by taking a decision-theoretic approach and acquiring the feature values which are expected to maximize some utility function (Saar-Tsechansky et al., 2009).”
Get another label? improving data quality and data mining using multiple, noisy labelers (2008, background): “For example, several authors [11, 12, 16, 17, 22, 32, 37] study the costly acquisition of feature information, assuming that the labels are known in advance.”