FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification

Keyphrases

• Class Imbalance 16%
• Class Imbalance Problem 16%
• Class Overlap 16%
• Classification Task 16%
• Complementary Advantages 16%
• Euclidean Distance 16%
• Feature Selection 16%
• Feature Weight 100%
• High-dimensional Setting 33%
• Hubness 16%
• Imbalanced Classification 100%
• Imbalanced Data 16%
• Minkowski Distance 16%
• Minority Class 16%
• Minority Sample 16%
• New Minorities 16%
• Oversampling Approach 100%
• Oversampling Technique 100%
• Pattern Recognition 16%
• Performance Improvement 16%
• Performance Prediction 16%
• Recognition Task 16%
• Redundant Variables 16%
• Resampling 16%
• Synthetic Minority 100%
• Weighted Metric 16%
• Weighted Minkowski 16%

Computer Science

• Class Imbalance 16%
• Class Imbalance Problem 16%
• Classification Task 16%
• Euclidean Distance 16%
• Feature Extraction 16%
• Feature Selection 16%
• Minkowski Distance 16%
• Minority Class 16%
• Pattern Recognition 16%
• Predictive Performance 16%
• Sampling Technique 100%

Mathematics

• Euclidean Distance 16%
• Minkowski 16%
• Oversampling 100%
• Pattern Recognition 16%
• Predictive Performance 16%
• Sampling Technique 100%