secom

Differential abundance (DA) and correlation analyses for microbial absolute abundance data

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Leakage-aware rare-event yield triage on UCI SECOM with time-based validation, review-budget metrics, uncertainty, and drift monitoring.

Root-cause attribution for SECOM lot failures: 590 signals down to a 3-signal shortlist, one confirmed

Reproducible SECOM fault detection with leakage-aware validation, root-cause candidates, FastAPI, PostgreSQL and Streamlit

Databricks ELT + anomaly detection pipeline for semiconductor quality using SECOM, PySpark/SQL, Delta Lake, and Isolation Forest with automated data quality checks.

Semiconductor yield analysis platform built on UCI SECOM dataset (1567 lots × 590 sensors, ~924K rows in PostgreSQL)

ML pipeline predicting wafer Pass/Fail from 590 SECOM sensors. Sister project to semicon-yield-dashboard.

scikit-learn analysis of the UCI SECOM wafer-yield dataset: feature ranking and classifiers.

Semiconductor manufacturing yield analysis using the UCI SECOM dataset, with preprocessing, feature selection, imbalanced classification, and explainability.