Imbalanced Data NearMiss for Comparison of SVM and Naive Bayes Algorithms
Imbalanced Data NearMiss for Comparison of SVM and Naive Bayes Algorithms Wawan Gunawan , Yudo Devianto , Anggi Puspita Sari Abstract The study aims to improve the diagnosis, management, and prevention of HIV/AIDS by using classification algorithms. The dataset used consists of 707,379 records and 89 columns. Data preprocessing includes removing irrelevant attributes, handling inconsistencies, and balancing the data using the NearMiss method, resulting in a balanced p........... Baca selengkapnya...
