Computational and Mathematical Methods in Medicine / 2017 / Article / Fig 6

Research Article

IPF-LASSO: Integrative -Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

Figure 6

Breast cancer data. (a) Integrated Brier score obtained with IPF-LASSO for different choices of penalty factors. The numbers associated with the points are the numbers of selected clinical and molecular variables, respectively. For example, “(3-18)” indicates that for the penalty factors the selected model includes 3 clinical variables and 18 molecular variables. (b) The negative partial likelihood against the parameter for different penalty factors. The colors of the curves are the colors of the corresponding points in (a).