Empirical Comparison of Approaches for Mitigating Effects of Class Imbalances in Water Quality Anomaly Detection

Computer Science

• Anomaly Detection 100%
• Class Imbalance 100%
• Neural Network Model 50%
• Learning Algorithm 50%
• Superior Performance 25%
• Performance Evaluation 25%
• Deep Neural Network 25%
• Evaluation Metric 25%
• Minority Class 25%
• Training Phase 25%
• Class Imbalance Problem 25%
• Fold Cross Validation 25%
• Learning State 25%
• Learning Philosophy 25%
• Ensemble Technique 25%
• Experimental Result 25%
• Classification Accuracy 25%
• Majority Class 25%
• Class Distribution 25%

Keyphrases

• Mitigating Effects 100%
• Class Imbalance 100%
• Approaches Comparison 100%
• Optimized Deep Neural Network 25%
• Homogeneous Ensemble 25%
• Heterogeneous Ensemble 25%
• Majority Class 25%
• Class Imbalance Problem 25%
• AUC Measure 25%
• Imbalanced Classes 25%
• Learning State 25%
• Training Phase 25%
• 5-fold Cross Validation 25%
• Learning philosophy 25%
• Imbalanced Class Distribution 25%