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. Author manuscript; available in PMC: 2024 Jul 5.
Published in final edited form as: Harv Data Sci Rev. 2024 Jan 31;6(1):10.1162/99608f92.9d86a749. doi: 10.1162/99608f92.9d86a749

Table B3.

Comparisons of median C-indices of six machine learning algorithms across varying censoring rates (40% to 80%) under a nonlinear log hazard model with various proportions of missing data for each covariate (0%, 10%, 20%). The table displays median C-index values from 100 experiments, along with their interquartile ranges.

Censoring Rate
40% 60% 70% 80%
0% Missing
Cox Model with Linear Log Hazards 65.6 (2.0) 67.8 (3.0) 69.0 (2.9) 72.5 (3.1)
Survival Support Vector Machines 73.0 (1.7) 74.6 (1.4) 76.3 (1.8) 78.7 (2.4)
Survival Gradient Boosting 72.6 (1.3) 74.2 (1.6) 75.7 (2.1) 78.0 (2.3)
Random Survival Forests 71.5 (1.5) 73.3 (1.6) 75.2 (2.0) 77.5 (1.9)
Naive Ensemble Averaging 71.5 (1.5) 73.4 (1.6) 75.3 (2.0) 77.6 (1.9)
Weighted Ensemble Averaging 73.1 (1.1) 74.8 (1.4) 76.6 (1.6) 78.9 (1.6)
10% Missing
Cox Model with Linear Log Hazards 64.5 (1.8) 66.3 (3.3) 67.9 (3.5) 70.8 (2.8)
Survival Support Vector Machines 70.7 (1.9) 72.3 (2.2) 73.5 (1.7) 75.9 (3.0)
Survival Gradient Boosting 69.9 (2.1) 71.4 (2.0) 73.0 (2.8) 74.7 (2.7)
Random Survival Forests 69.6 (1.6) 71.3 (2.5) 72.8 (2.8) 75.1 (2.3)
Naive Ensemble Averaging 69.6 (1.6) 71.4 (2.5) 72.8 (2.9) 75.2 (2.4)
Weighted Ensemble Averaging 70.9 (1.4) 72.5 (2.1) 74.4 (2.4) 76.4 (2.5)
20% Missing
Cox Model with Linear Log Hazards 63.8 (2.0) 65.6 (3.2) 66.0 (3.4) 69.4 (4.0)
Survival Support Vector Machines 68.9 (2.1) 70.6 (2.4) 71.5 (2.3) 73.5 (3.9)
Survival Gradient Boosting 67.8 (1.9) 70.1 (2.9) 70.0 (3.3) 72.9 (3.9)
Random Survival Forests 68.1 (2.0) 69.7 (2.0) 70.9 (3.3) 73.0 (3.9)
Naive Ensemble Averaging 68.1 (2.0) 69.8 (2.0) 71.0 (3.3) 73.1 (4.0)
Weighted Ensemble Averaging 69.2 (1.5) 71.0 (2.2) 72.0 (2.9) 74.5 (3.5)