# 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.