Fig. 4: Examples of actionable paths planned on synthetic dataset.
From: Health improvement framework for actionable treatment planning using a surrogate Bayesian model
The optimal paths for improving the response variable predicted by the ML model are represented for randomly selected two examples: instance A (a–c) and instance B (d–f). a, d The orders of changes in the explanatory variables in the optimal path and the accompanying changes in the predicted values. In the transition steps, the upward or downward arrow represents a unit increase or decrease in the explanatory variable, respectively. b, e Two-dimensional (2D) plots of the path. The 2D plots are shown regarding the selected two variables: X1 and X2 (b), and X2 and X3 (e). In the heatmaps, the probability density of the actual data, normalized by the panel with the maximum number of data, is expressed. c, f Three-dimensional (3D) plots of the path.
