Lung Cancer Classification Using the Extreme Gradient Boosting (XGBoost) Algorithm and Mutual Information for Feature Selection

Lung Cancer Classification Using the Extreme Gradient Boosting (XGBoost) Algorithm and Mutual Information for Feature Selection

Lung cancer is one of the deadliest types of cancer worldwide and is often detected too late due to the absence of early symptoms. This study aims to evaluate the impact of feature selection using Mutual Information on the performance of lung cancer classification with the XGBoost algorithm. Mutual...

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Bibliographic Details
Main Authors: Regitha Zizilia, Yulison Herry Chrisnanto, Gunawan Abdillah
Format: Article
Language:Indonesian
Published: Islamic University of Indragiri 2025-09-01
Series:Sistemasi: Jurnal Sistem Informasi
Subjects:
classification
lung cancer
mutual information
xgboost
k-fold cross validation
Online Access:https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5345
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