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README.md

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+---
+language: en
+tags:
+- machine-learning
+- classification
+- predictive-maintenance
+- engine-condition
+- scikit-learn
+datasets:
+- dhani10/engine-condition-dataset
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+- roc_auc
+---
+
+# Engine Condition Prediction Model
+
+This model predicts engine condition (Normal=0 / Faulty=1) from sensor signals for predictive maintenance.
+
+## Model Details
+- **Winning Model**: Random Forest
+- **Training Data**: dhani10/engine-condition-dataset
+- **Input Features**: ['Engine rpm', 'Lub oil pressure', 'Fuel pressure', 'Coolant pressure', 'lub oil temp', 'Coolant temp']
+- **Target**: Engine Condition (0=Normal, 1=Faulty)
+- **Training Samples**: 15628
+- **Test Samples**: 3907
+- **Registered**: 2025-11-07T07:50:04.426743+00:00
+
+## Cross-Validation
+- **Best CV Score**: 0.7724
+
+## Test Set Performance
+- **Accuracy**: 0.6596
+- **F1-Score**: 0.7684
+- **Precision**: 0.6728
+- **Recall**: 0.8957
+- **ROC-AUC**: 0.6992
+
+## Best Hyperparameters
+```json
+{
+  "classifier__max_depth": 5,
+  "classifier__n_estimators": 100
+}