| tags: | |
| - sklearn | |
| - predictive-maintenance | |
| - classification | |
| - automotive | |
| library_name: sklearn | |
| license: apache-2.0 | |
| pipeline_tag: text-classification | |
| # Engine Predictive Maintenance Model | |
| **Best model:** `GradientBoosting` | |
| **F1 (test):** 0.7657 | |
| ## Usage | |
| ```python | |
| import pickle, pandas as pd | |
| with open('best_model.pkl', 'rb') as f: | |
| model = pickle.load(f) | |
| # X = pd.DataFrame([{ | |
| # 'engine_rpm': 2500, 'lub_oil_pressure': 4.2, 'fuel_pressure': 110, | |
| # 'coolant_pressure': 1.2, 'lub_oil_temp': 95, 'coolant_temp': 88 | |
| # }]) | |
| # pred = model.predict(X)[0] | |
| ``` | |
| ## Notes | |
| - Tuned via GridSearchCV (scoring=F1), metrics logged with MLflow. |