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2012
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Sampling Strategies to Evaluate the Performance of Unknown Predictors

9 years 8 months ago
Sampling Strategies to Evaluate the Performance of Unknown Predictors
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampling. We are particularly interested in studying the sampling strategies for problems in which the prevalence of the two classes is highly biased toward one of the classes. The evaluation measures of interest we want to estimate as accurately as possible are those obtained from the contingency table. We provide a careful theoretical analysis on sensitivity, specificity, and precision and show how sampling strategies should be adapted to the rate of skewness in data in order to effectively compute the three aforementioned evaluation measures.
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrech
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where SDM
Authors Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht
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