The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) represent a logistic regression classifier’s model performance by depicting the trade−off rates between TPs ...

The ROC curve is plotted by the GPLOT procedure, and the plot is shown in Output 39.6.3. symbol1 i=join v=none c=blue; proc gplot data=roc1; title 'ROC Curve'; plot _sensit_*_1mspec_=1 / vaxis=0 to 1 ...

The CATMOD procedure can perform linear regression and logistic regression of response functions for data that can be represented in a contingency table. See Chapter 5, "Introduction to Categorical ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...

The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...