From: Disease risk analysis for schizophrenia patients by an automatic AHP framework
Methods | Hyper-parameters |
---|---|
Random Forest | num of trees: 1000, num of attr consider at each split: 5 |
Neural Network | Neurons of hidden layers: 100, activation: Relu, solver: Adam, regularization, learning rate: 0.001, iters: 200 |
Logistic Regression | regularization type: ridge(L2), strength: C = 1 |
SGD | Loss function: logistic regression, regularization method: Elastic Net, \(\epsilon\): 0.1, iters:1000 |
kNN | K: 9, metric: Euclidean, weight: Uniform |
SVM | RBF, Kernel:\(exp(-g|x-y{|}^{2})\), C: 1.00,: 0.1, iteration limit: 100 |