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Drift-Robust Gas Classification Analysis by Vineet Rathi is a document available to read on EtoBox.

This document discusses the challenges of gas classification using metal-oxide (MOX) electronic-nose systems, particularly focusing on the impact of temporal drift on model performance. The study utilizes the UCI Gas Sensor Array Drift dataset to evaluate drift-robust classification methods, employing a time-aware evaluation approach across different batches. Results indicate that logistic regression without scaling performed best on future test data, highlighting the importance of addressing distribution s

Author
Vineet Rathi
Language
EN