Many repeated manual feature adjustments and much heuristic parameter tuning are required during the debugging of machine learning (ML)-based transient stability assessment (TSA) of power systems. Furthermore. the results produced by ML-based TSA are often not explainable. This paper handles both the automation and interpretability issues of ML-based TSA. https://www.markbroyard.com/deal-time-gtech-airram-mk2-k9-roller-roll-brush-bar-filter-vacuum-cleaner-hot-on-sale-best-find/