IEEE Region 5

[] Free Registration (with a Zoom account; you can get one for free if you don't already have it): https://sjsu.zoom.us/meeting/register/tZcsc-CoqjwpG9aPDHfg6Axqvn90i4uQRmqr Synopsis: For a long time, the AI/ML community relied on traditional evaluation metrics such as the confusion matrix, accuracy, precision, and recall for assessing the performance of machine learning models. However, the rapidly evolving field has been raising several ethical concerns, which calls for a more comprehensive evaluation scheme. In easy-to-understand language, this talk will delve into the quantitative analysis of model performance, emphasizing the critical importance of explainability. As ML models become increasingly complex and pervasive, understanding their decision-making processes is paramount. We'll explore various performance metrics, their limitations, and the growing need for transparency. Topics covered include Cohen’s Kappa Statistic, Matthew's correlation coefficient (MCC), Confusion Matrix, Precision, Recall, G-measure, ROC Curve, Youden's J statistic, Type II Adversarial attack, R-squared, LIME, SHAP, and more. Speaker(s): Dr. Vishnu S. Pendyala Virtual: https://events.vtools.ieee.org/m/442073

See the 2025 Lone Star Section planning calendar and agenda attached to this announcement. Agenda: · Call to Order & Introductions Review 2025 Lone Star Section Planning Calendar Secretary’s Report November ExCom Minutes Treasurer’s Report South Area Chair Report Member Development Elections Conferences 2025 Carnahan (ICCST) 2026 MILCOM Government Relations IEEE-USA & CVD Local Recent Events Volunteer appreciation dinner December 5, 2024 LSS logo shirts for volunteer leaders LSS 5th anniversary coffee mugs Upcoming Events MGA reporting deadline Engineers Week (February 16-22, 2025) Communications Other New Business Action Items Help Wanted – Newsletter Editor, Awards Chair & others. Next Meeting: 5 February 2025 Room: CR 1.102, Bldg: 168, Southwest Research Institute, 6220 Culebra Road, San Antonio, Texas, United States, 78238, Virtual: https://events.vtools.ieee.org/m/455800