Table 3 Adjusting modeling parameters
Setting parameters | Model | Abbreviations |
|---|---|---|
– | Naïve Bayes | NB |
Index split = 4 | Decision tree | DT |
Level of confidence for pruning = 0.25 | ||
Minimum number of samples in each leaf = 2 | ||
The maximum depth of the tree = 50 | ||
The number of hidden layers = 1 | Neural network | ANN |
Learning rate = 0.3 | ||
Momentum rate = 0.2 | ||
Number of training cycles = 300 | ||
Core rate = X*Y | Support vector machine | SVM |
Constant = 0 | ||
The number of repetitions = 10 | Ada boost-Naïve Bayes | Ada-NB |
The number of repetitions = 10 | Ada boost-decision tree | Ada-DT |
The number of repetitions = 10 | Ada boost-neural network | Ada-NN |
The number of repetitions = 10 | Ada boost-support vector machine | Ada-SVM |