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What Subha demonstrated
Built a leakage-aware turbine yield predictor end to end: framed TEY as the target, excluded downstream CO/NOx emissions, trained a LinearRegression baseline and a RandomForest model, and evaluated them on a time-based held-out split. The final model achieved 1.532 MWh MAE, 1.937 RMSE, and 0.9833 R2 on held-out data, with a residual read and a concise model card covering intended use, limits, and monitoring.
- Leakage-Free Feature Selection
- Honest Held-Out Evaluation
- Model Comparison Against Baseline
- Plain-Language Model Communication
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