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Criteria used for performing the predictive performance of the model were accuracy rate, positive predictive value, negative predictive value, false-positive rate, and false-negative rate computed from test data according to the LOOCV methodology.
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The logistic model performance characteristics were accuracy 65.2% (model correctly classified 4,406 of 5,450 subjects), sensitivity 66.1% and specificity of 62.2%.
We investigated whether these co-variates affect the parameters of the HSROC model, that is, accuracy, threshold, and shape.
Comparisons with the experimental results show this model is rather accuracy in frequency calculation.
37 The most common criterion for evaluating the performance of a statistical model is its accuracy in terms of data fit.
Two binominal mixed effects model were fitted on the accuracy of T1 with Task entered as fixed factor.
It has been shown that this simple model is of sufficient accuracy for engineering applications.
In order to examine the effect of Task on the AB, a binominal mixed effect model was fitted on accuracy scores of T2 given correct report of T1.
The R-square of the model was 0.90, the accuracy factor was 0.82.
Accuracy of this fuzzy model was compared with the accuracy of a statistical regression model.
The performance of the models were evaluated for accuracy, misclassification error rate, sensitivity and specificity.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com