A hybrid classifier combining Borderline-SMOTE with AIRS algorithm for estimating brain metastasis from lung cancer: A case study in Taiwan. Issue 2 (April 2015) - Wang, Kung-Jeng; Adrian, Angelia Melani; Chen, Kun-Huang; Wang, Kung-Min
Highlights Developing a new classifier approach by combining borderline SMOTE and AIRS. Eight medical datasets from UCI machine learning repository were evaluated. Outperform well-known classifiers. The proposed method can handle imbalanced class problems efficiently. Applying successfully to the prediction of lung cancer to brain metastasis.