Fig. 9
From: Comparing regression modeling strategies for predicting hometime
Partial dependence plots depicting the relationship between stroke severity (measured using the PaSSV score) and predicted 90-day hometime across the test data set using seven different machine learning models. (A Random forests regression; B Bagged regression trees; C Support vector regression; D Generalized boosting machine (Gaussian distribution, interaction depth = 2); E Generalized boosting machine (Poisson distribution, interaction depth = 15)); F Lasso regression; G Ridge regression