A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

• 主要な著者: Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana
• フォーマット: 論文
• 言語: English
• 出版事項: Institute of Advanced Engineering and Science 2021
• 主題: QA75 Electronic computers. Computer science
• オンライン･アクセス: http://repo.uum.edu.my/27849/1/IJEECS%2020%201%202021%20412%20419.pdf; http://repo.uum.edu.my/27849/; http://ijeecs.iaescore.com/index.php/IJEECS/article/view/22253

Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. However, real world applications commonly involved imbalanced class problem where the classes have different importance. This condition impeded the entropy-based heuristic of existing A...