<p>Accuracies are estimated by cross-validation on the calibration data using class-wise normalized loss function (chance level = 0.5). Each colored '*' represents the accuracy for each participant in giving conditions. The edges of the blue box in each column reveal the 25% and 75% data range. The central red mark is the median accuracy overall the participants in the giving condition.</p
<p>Simulated calibration represented as accuracies computed by increasing the number of trials of th...
<p>For each subject and condition, one row depicts the estimated sliding binary classification accur...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>The binary classification accuracy, estimated with cross validation is plotted for each condition...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<p>Accuracies are mean accuracies of test set performance over ten folds. (* 0.001</p
Boxplot of 6 fold (5 fold for 4 subjects) out-of-sample classification accuracies from real data of ...
<p>A. Behavioral and Subject dependent (within subject classification) LOO (leave one out) Classific...
<p>The number of selected reliable samples and the corresponding classification accuracy when probab...
<p>Each gray line shows the accuracy difference when one subject’s deceptive data is used as test, a...
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
Comparison of mean estimation error performance across trial conditions in A) the discovery and B) t...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
The average cross validation ACC with 95% CI and ACC on the external validation set are reported. Be...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Simulated calibration represented as accuracies computed by increasing the number of trials of th...
<p>For each subject and condition, one row depicts the estimated sliding binary classification accur...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>The binary classification accuracy, estimated with cross validation is plotted for each condition...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<p>Accuracies are mean accuracies of test set performance over ten folds. (* 0.001</p
Boxplot of 6 fold (5 fold for 4 subjects) out-of-sample classification accuracies from real data of ...
<p>A. Behavioral and Subject dependent (within subject classification) LOO (leave one out) Classific...
<p>The number of selected reliable samples and the corresponding classification accuracy when probab...
<p>Each gray line shows the accuracy difference when one subject’s deceptive data is used as test, a...
<p>The table shows the cross-validation performance of our method on the labeled data points. The me...
Comparison of mean estimation error performance across trial conditions in A) the discovery and B) t...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
The average cross validation ACC with 95% CI and ACC on the external validation set are reported. Be...
<p>Performance comparisons of multiple individual classifiers on the training dataset by 10-fold cro...
<p>Simulated calibration represented as accuracies computed by increasing the number of trials of th...
<p>For each subject and condition, one row depicts the estimated sliding binary classification accur...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...