| # Engine Predictive Maintenance - AdaBoost Model | |
| ## Model Summary | |
| This model predicts whether an engine requires maintenance based on engine sensor readings. | |
| ## Final Selected Model | |
| AdaBoost | |
| ## Input Features | |
| - engine_rpm | |
| - lub_oil_pressure | |
| - fuel_pressure | |
| - coolant_pressure | |
| - lub_oil_temp | |
| - coolant_temp | |
| ## Best Hyperparameters | |
| {'learning_rate': 0.05, 'n_estimators': 150} | |
| ## Performance on Test Data | |
| - Accuracy: 0.6540 | |
| - Precision: 0.6537 | |
| - Recall: 0.9594 | |
| - F1 Score: 0.7776 | |
| ## Business Relevance | |
| The model is intended for predictive maintenance scenarios where early detection of engine faults helps reduce downtime, avoid unexpected breakdowns, and optimize maintenance planning. | |