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Several classifiers are learned from the feature samples and the reference attention data, and model accuracy is computed on the test data set Fig. 5 Examples of final feature set for test person 6. Image (a) represents a single frame of Kinect video with visualization of Kinect data including face rectangles, face points, gaze vectors, and body skeletons.
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This accuracy was computed on the test set comprising another 5 male's and 5 female's testimonies.
Accuracy was computed on all trials included in the analysis.
Predicting accuracy is computed based on leave-one-out or 10 fold cross-validation using biomarkers identified in each method.
Sensitivity, specificity, precision and accuracy were computed for each sample.
However, average classification accuracy is computed from the accuracy obtained from each individual feature.
The estimated accuracy is computed as the average accuracy over the n test sets.
For each s0, the accuracy was computed.
In total, accuracy was computed from 24 data samples per condition (30 total conditions).
Accuracy was computed as the correlation of the true genotypes from sequence calls and imputed dosages.
Beam Constraint Tree Model is computed on the basis of Linear Tree Model, and can achieve higher accuracy.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com