An Adaptive Pre-clustering Support Vector Machine for Binary Imbalanced Classification

Keyphrases

• Support Vector Machine 100%
• Imbalanced Classification 100%
• Clustering Support Vector Machine 100%
• Pre-clustering 100%
• Undersampling 40%
• Density Peaks 40%
• Machine Learning 20%
• Fast Search 20%
• Artificial Intelligence 20%
• Public Evaluation 20%
• Intelligence Learning 20%
• Efficient Classification 20%
• Area under the Curve 20%
• EasyEnsemble 20%
• Oversampling Technique 20%
• Accurate Classification 20%
• Classification Performance 20%
• K-means 20%
• Public Dataset 20%
• Adaptive Clustering 20%
• Peak Detection 20%
• F-measure 20%
• G-mean 20%
• Structural Risk Minimization 20%
• Support Vector Machine Classification 20%
• Rebalance 20%
• Fuzzy C-means 20%
• Sample Space 20%
• Adaptive Density 20%
• Dataset Distribution 20%
• Cluster Centroid 20%
• Support Modification 20%
• Synthetic Minority 20%

Mathematics

• Support Vector Machine 100%
• Clustering 25%
• Superiority 12%
• Sampling Technique 12%
• K-Means 12%
• Structural Risk Minimization 12%
• Sample Space 12%
• Centroid 12%

Computer Science

• Support Vector Machine 100%
• Artificial Intelligence 12%
• Machine Learning 12%
• Support Vector Machine 12%
• Sampling Technique 12%
• Classification Performance 12%
• Risk Minimization 12%
• Cluster Centroid 12%