Table 5 An overview of the hyperparameters.
From: A cross dataset meta-model for hepatitis C detection using multi-dimensional pre-clustering
Model | Hyperparameter | Range |
|---|---|---|
XGBoost | Learning rate | [0.1, 0.3] |
N estimators | [100, 300] | |
Max depth | [3, 5, 7] | |
Subsample | [0.6, 0.8, 1.0] | |
Colsample bytree | [0.6, 0.8, 1.0] | |
KNN | N neighbors | [3, 5, 7, 9, 11] |
Weights | [‘uniform’, ‘distance’] | |
Algorithm | [‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’] | |
p | [1, 2] | |
SVM | C | [0.1, 1, 10, 100] |
Kernel | [‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’] | |
gamma | [‘scale’, ‘auto’] | |
degree | [2, 3, 4, 5] | |
Random forest | N estimators | [100, 300] |
Max depth | [None, 10, 20] | |
Min samples split | [2, 5] | |
Min samples leaf | [1, 2] |
