A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification

Keyphrases

• Undersampling 100%
• Imbalanced Classification 100%
• Popular 50%
• Algorithm Performance 16%
• Training Data 16%
• Resampling 16%
• Classification Accuracy 16%
• Area under the Curve 16%
• Majority Class 16%
• EasyEnsemble 16%
• Noise Filtering 16%
• Performance Ratio 16%
• F-measure 16%
• G-mean 16%
• Class Imbalance Problem 16%
• Higher Classification 16%
• Significance Analysis 16%
• Data Preprocessing Technique 16%
• RUSBoost 16%
• AdaBoost 16%
• Benchmark Dose 16%
• Balanced Dataset 16%
• UnderBagging 16%
• Imbalance Ratio 16%

Computer Science

• Sampling Scheme 100%
• Experimental Result 50%
• Algorithm Performance 50%
• Training Dataset 50%
• Majority Class 50%
• Data Preprocessing 50%
• Class Imbalance Problem 50%