I-spline Smoothing for Calibrating Predictive Models.
We proposed the I-spline Smoothing approach for calibrating predictive models by solving a nonlinear monotone regression problem. We took advantage of I-spline properties to obtain globally optimal solutions while keeping the computational cost low. Numerical studies based on three data sets showed the empirical evidences of I-spline Smoothing in improving calibration (i.e.,1.6x, 1.4x, and 1.4x on the three datasets compared to the average of competitors-Binning, Platt Scaling, Isotonic Regression, Monotone Spline Smoothing, Smooth Isotonic Regression) without deterioration of discrimination.
Division of Biomedical Informatics, University of California at San Diego, La Jolla, California 92093.
Yuan
Y
Wu
Xiaoqian
X
Jiang
Jihoon
J
Kim
Lucila
L
Ohno-Machado