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PERBANDINGAN LOGISTIC REGRESSION DAN XGBOOST DALAM KLASIFIKASI KONDISI MENTAL…
Accurate mental state identification is important across various fields, and EEG is a biomedical signal widely used for this purpose as it can directly and non-invasively record brain electrical activity. However, the complex, nonlinear, and high-dimensional characteristics of EEG signals require effective classification methods. This study aims to implement and compare the performance of Logis…
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- xiv, 108 hlm.; ilus.; tab.; 29 cm.
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- T2010352026
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