Table 3 Tuned parameters for the prediction models.
From: Machine learning-based prediction of drug response in ischemia reperfusion animal model
Classifier | Parameter | Value |
|---|---|---|
RF | # trees | 100 |
Maximum depth per tree | 10 | |
kNN | k | 5 |
Weight | Uniform | |
NN | Type | MLP |
# Hidden layers | 2 | |
# Neurons per hidden layer | (6, 4) | |
Solver | “lbfgs” optimizer | |
SVM | Regularization parameter (C) | 1 |
Stopping tolerance | 0.0001 | |
LR | # Iterations (max) | 100,000 |
Stopping tolerance | 0.0001 | |
SFS | Estimator | RF |
Direction | Forward | |
Stopping tolerance | 0.00001 | |
Cross validation | 5 Iterations |
