A cluster-based intelligence ensemble learning method for classification problems

Keyphrases

• Cluster-based 100%
• Classification Problem 100%
• Ensemble Learning Method 100%
• Clustering Methods 75%
• Ensemble Learning 50%
• Result Prediction 50%
• Structure Analysis 25%
• Machine Learning 25%
• Classification Methods 25%
• Classification Performance 25%
• Validation Experiment 25%
• Parameter Sensitivity 25%
• Machine Learning Techniques 25%
• Cluster Structure 25%
• Support Vector Machine 25%
• Classification Model 25%
• Classification Algorithms 25%
• Naïve Bayes 25%
• Benchmark Dataset 25%
• Base Classifier 25%
• 10-fold Cross Validation 25%
• Cluster Classification 25%
• Clustering Ensemble 25%
• Swarm Intelligence Algorithm 25%
• Random Forest 25%
• Learning Patterns 25%
• Unknown Categories 25%
• Popular 25%
• K-nearest 25%

Computer Science

• Ensemble Learning 100%
• Classification Problem 100%
• Clustering Method 75%
• Machine Learning 50%
• Learning System 50%
• Classification Models 25%
• Random Decision Forest 25%
• Base Classifier 25%
• Swarm Intelligence Algorithm 25%
• Support Vector Machine 25%
• Classification Performance 25%
• Classification Method 25%
• Classification Algorithm 25%
• Cluster Structure 25%
• Sensitivity Parameter 25%

Mathematics

• Clustering Method 100%
• Classification Problem 100%
• Support Vector Machine 33%
• Cross-Validation 33%
• Nearest Neighbour 33%
• Naïve Bayes 33%
• Classification Method 33%
• Swarm Intelligence 33%