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- W4386953522 abstract "The first machine learning system was developed in the 1950s to play checkers. It was followed by the invention of the nearest neighbor algorithm, which allowed computers to recognize patterns. Today, there are numerous machine learning models available, each with its unique strengths and weaknesses. This study has compared some of the most well-known models to identify the best one. To ensure a comprehensive comparison, we have used a correlation matrix and eliminated highly correlated attributes. After comparing the models, we have used the SHAP (Shapely Additive explanations) method for qualitative analysis to investigate the success of the best-performing models." @default.
- W4386953522 created "2023-09-23" @default.
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- W4386953522 creator A5092921410 @default.
- W4386953522 date "2023-07-19" @default.
- W4386953522 modified "2023-09-27" @default.
- W4386953522 title "Comparative explainable Machine learning to evaluate Bank marketing success" @default.
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- W4386953522 doi "https://doi.org/10.1109/iceccme57830.2023.10252843" @default.
- W4386953522 hasPublicationYear "2023" @default.
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