|
Model
|
Nbins
|
Mtry
|
Ntree
|
Max depth
|
|---|
|
Random forest
|
20, 30, 40 (numeric)
|
5, 10, 15
|
200
|
5, 10, 15
|
| |
3 (categorical)
| | | |
| |
Nbins
|
Learn rate
|
ntree
|
Max depth
|
Sample rate
|
|---|
|
Gradient boosting machine
|
20, 30, 40 (numeric)
|
0.1, 0.001
|
250, 700
|
5, 10
|
0.7, 0.8, 0.9
|
|
3 (categorical)
|
| |
Lambda
|
Alpha
|
|---|
|
Logistic regression and super learner
|
Range exp(−11) to exp(6)
|
0–1 by 0.025
|
-
Nbins number of bins, Mtry number of splits in branches, Ntree total number of trees grown, Max depth maximum depth to grow the trees (for a detailed description of the model parameters and how they are used see Additional file 3)
