Engine Health Predictive Maintenance Model

This model predicts whether an engine requires maintenance based on sensor readings.

Model

Best model: Logistic Regression

Target

  • 0: Normal engine condition
  • 1: Faulty / maintenance required

Business Metric

Recall was prioritized because missing unhealthy engines can cause breakdowns, downtime, and repair cost.

Evaluation Results

  • Accuracy: 0.6415
  • Precision: 0.5111
  • Recall: 0.6886
  • F1-Score: 0.5867
  • ROC-AUC: 0.7002
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