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What Muhammad demonstrated
Built a compact rolling-bearing fault detector end to end: visualized the vibration snapshot, engineered time-domain features, trained a shallow decision tree on training bearings only, and evaluated it on a held-out set with catch-rate and false-alarm metrics. The decision memo justified a 0.41 alarm threshold using explicit miss-vs-false-alarm costs and correctly localized the fault to the outer race from the dominant BPFO energy.
- Leakage-Free Feature Engineering
- Honest Model Evaluation
- Cost-Based Decision Making
- Interpreting Defect Frequencies
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