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The performances of the class-specific predictors are evaluated using different datasets formed by face images and natural-scene images.
In (Keung et al. 2013), ninety predictors are evaluated with 20 datasets, they used 7 performance measures to determine stable rankings of different predictors.
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Using the Stepwise Discriminant Analysis, the best predictors were evaluated from basic soil classification parameters.
Fifteen articles were considered eligible for inclusion and 23 predictors were evaluated in more than one study in men and/or women.
Preterm birth predictors were evaluated using traditional statistical and newer data mining analyses.
The candidate predictors were evaluated using backward elimination in regression models.
These predictors were evaluated on ten challenging test cases.
The incremental contributions of polynomial terms in the predictors were evaluated by the likelihood ratio test.
The performances of the TMH predictors were evaluated with four different scores.
Short-term cardiac outcome predictors were evaluated.
Finally, the long-term QoL predictors were evaluated.
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