Table 4.
Key features listed in descending order of importance.
| Service feature | Logistic regression (coefficienta) | Decision tree (level of splits) | Gradient boost (importance, %) | Random forest (importance, %) |
| 1 | Response rate (−13.89) | Offline connection (1) | Offline connection (30) | Offline connection (24) |
| 2 | Offline connection (−4.99) | Social return (2) | Total dialog (30) | PriorExam (20) |
| 3 | Social return (−3.11) | Total dialog (2) | Response rate (25) | Total dialog (18) |
| 4 | Patient posts (−2.63) | Private (3) | Social return (8) | Response rate (17) |
| 5 | Total dialog (2.47) | Response rate (3) | Private (6) | Patient post (9) |
| 6 | PriorExam (1.70) | PriorExam (4) | Patient posts (1) | Social return (7) |
| 7 | Private (−0.99) | Answer_frq (4) | PriorExam (0) | Private (2) |
| 8 | Ranking 2 (−0.305) | Patient posts (6) | Answer_frq (0) | Answer_frq (2) |
| 9 | Answer_frq (−0.14) | Question_frq (6) | Question_frq (0) | Question_frq (1) |
| 10 | Question_frq (−0.13) | Ranking 2 (8) | Title1 (0) | Title1 (0) |
| 11 | Title1 (−0.089) | Title 1 (9) | Ranking 2 (0) | Ranking 2 (0) |
aFor logistic regression, a regularization procedure (see Multimedia Appendix 2) is applied, so large weight coefficients are penalized for avoiding overfitting. All coefficients are significant (P<.001).