Identifying clusters structure of rare events using random forest clustering

• Main Authors: Zaturrawiah A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, Norhafiza Hamzah
• Format: Proceedings
• Language: English; English
• Published: Faculty of Science and Natural Resources 2021
• Subjects: QA76.75-76.765 Computer software
• Online Access: https://eprints.ums.edu.my/id/eprint/32160/1/Identifying%20clusters%20structure%20of%20rare%20events%20using%20random%20forest%20clustering.ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32160/2/IDENTIFYING%20CLUSTERS%20STRUCTURE%20OF%20RARE%20EVENTS%20USING%20RANDOM%20FOREST%20CLUSTERING.pdf; https://eprints.ums.edu.my/id/eprint/32160/; https://drive.google977-2-73-522200-2.com/file/d/1zKEpSiYvg9vZHHzuKra49512D_AMLubu/view

Given highly imbalanced data, most learning algorithms faced the challenge to accurately predict rare events, while such cases were the ones that carry importance and useful knowledge. In a binary class label dataset, the rare events are the ones in the minority class. This study used a stroke datas...