Publikasi Ilmiah STMIK Banjarbaru
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Utilizing Explainable AI for Interpreting Machine Learning Model Results in Ceria Credit Scoring
This study aims to improve the transparency of machine learning models in credit scoring using various Explainable Artificial Intelligence (XAI) methods. The methods used include SHAP, BRCG, ALE, Anchor, and ProtoDash to explain the prediction results of machine learning models, namely logistic regr
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