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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Explanation of the local contribution of EEG features through the Eli5 model in classifying a single test instance (predicted class = Stroke) using the XGBoost model. The importance of the features is denoted by positive contribution.