Machine learning algorithm | Parameter grid |
---|---|
Random Forest | |
\(\bullet\) ’max_depth’: 10, 150, 500, 1000, | |
\(\bullet\) ’max_features’: 30, 500, 3000, | |
\(\bullet\) ’min_samples_leaf’: 1, 10, 100, | |
\(\bullet\) ’min_samples_split’: 2, 10, 100, | |
\(\bullet\) ’n_estimators’: 10, 100 | |
Linear Support Vector Machine | |
\(\bullet\) ’loss’: ’hinge’, | |
\(\bullet\) ’penalty’: ’l2’, | |
\(\bullet\) ’alpha’: 1e-3, | |
\(\bullet\) ’random_state’: 42, | |
\(\bullet\) ’max_iter’: 5, | |
\(\bullet\) ’tol’: None | |
Logistic Regression | |
\(\bullet\) ’n_jobs’: 1, | |
\(\bullet\) ’C’: 1 | |
Neural Network (BERT) | |
\(\bullet\) ’batch_size’: 3, | |
\(\bullet\) ’lr’: 1e-5, | |
\(\bullet\) ’eps’: 1e-8, | |
\(\bullet\) ’epochs’: 5, | |
\(\bullet\) ’seed_val’: 17 |