From: Estimating predictive stimulus features from psychophysical data: The decision image technique applied to human faces Journal of Vision. 2010;10(5):22. doi:10.1167/10.5.22 Figure Legend: Comparing the performance of the decision model estimated using logistic regression with other estimation methods; the diagonal lines in each of the subplots mark the equal performance contour. Top row: Comparison of the average deviance of the logistic regression model with those of the prototype model, the Fisher discriminant model, and the support vector machine (from left to right). For each of the four conditions and seven subjects, the logistic regression model outperforms the three alternative models. Second row: Scatter plots of the rank-correlations of the model-predictions with the subjects' predictions. Bottom row: Scatter plots of the partial rank-correlation between the predicted and observed probabilities after conditioning on the true gender of each stimulus. Partial rank-correlation conditioned on the true gender show how well a model predicts the exact decision probabilities and not just the gender; see text for details. Date of download: 11/6/2017 The Association for Research in Vision and Ophthalmology Copyright © 2017. All rights reserved.