Table 3 Details of ML and decomposition models structures for predicting the river water level.
From: Prediction of the monthly river water level by using ensemble decomposition modeling
Sr. No | Model | Configuration |
|---|---|---|
First combination | ||
1 | Super vector machine (SVM) | kernel = ’linear’, C = 1.0, epsilon = 0.1 |
2 | SVM (regularization) | kernel = ’rbf’, C = 2 |
3 | Random Forest | random state = 100 |
4 | Random Sub-space | num_subspaces = 10, n_estimators = 6, random_state = 123 |
Second combination | ||
5 | SVM linear-CEEMDAN | Hyper-parameters: n_estimators = 100, Random state = 100 |
6 | SVM RBF-CEEMDAN | Hyper-parameters: n_estimators = 100, Random state = 100 |
7 | Random Forest -CEEMDAN | Hyper-parameters: n_estimators = 100, random state = 100 |
8 | Random subspace-CEEMDAN | Hyper-parameters: : n_estimators = 15, Random state = 100 |
