Table 7 Comparison with other machine learning methods
From: Machine learning-based turbulence-risk prediction method for the safe operation of aircrafts
Method | TP | TN | FP | FN | Model |
|---|---|---|---|---|---|
Proposed method | 148 | 14 | 1 | 2 | Use statistical analysis as well |
Tree | 158 | 4 | 3 | 0 | Fine tree, medium tree, coarse tree |
LDA | 160 | 2 | 3 | 0 | Linear discriminant |
Logistic regression | 162 | 0 | 3 | 0 | Â |
Kernel Naive Bayes | 162 | 0 | 3 | 0 | Kernel Naive Bayes, kernel type: Gaussian |
SVM | 162 | 0 | 3 | 0 | Linear SVM, quadratic SVM, cubic SVM, fine Gaussian SVM, medium Gaussian SVM, coarse Gaussian SVM |
KNN | 162 | 0 | 3 | 0 | Fine KNN, medium KNN, coarse KNN, cosine KNN, cubic KNN, weighted KNN |
Ensemble | 162 | 0 | 3 | 0 | Boosted trees, bagged trees, subspace discriminant, subspace KNN |
Neural network | 161 | 1 | 3 | 0 | Narrow neural network, medium neural network, wide neural network, bilayered neural network, trilayered neural network |
Kernel | 159 | 3 | 3 | 0 | SVM kernel, logistic regression kernel |