An efficient churn prediction model using gradient boosting machine and metaheuristic optimization

Engineering

• Classification Performance 50%
• Comparative Analysis 50%
• Effective Solution 50%
• Initial Classification 50%
• Local Optimum 50%
• Loss Function 50%
• Metaheuristic Optimization 100%
• Metrics 50%
• Optimization Method 50%
• Particle Swarm Optimization 100%
• Quantitative Evaluation 50%
• Radial Basis Function 50%
• Robust Solution 50%
• Support Vector Machine 50%
• Telecommunication 100%

Keyphrases

• Artificial Ecosystem-based Optimization 10%
• Churn Prediction 100%
• Classification Performance 10%
• Comparative Analysis 10%
• Customer Churn 10%
• Decision Tree 10%
• Effective Solutions 10%
• Enhanced Gradient 60%
• Exponential Loss 10%
• GBM Model 10%
• Gradient Boosting Machine 100%
• Gradient Boosting Model 60%
• Hyperparameters 10%
• Learning Process 10%
• Local Optimum 10%
• Loss Function 10%
• Machining Optimization 100%
• Metaheuristic Optimization 100%
• Optimization Methods 10%
• Particle Swarm Optimization 20%
• Performance Enhancement 10%
• Prediction Method 10%
• Premature Convergence 10%
• Quantitative Metrics 10%
• Rank Test 10%
• RBF Kernel 10%
• Robust Solution 10%
• State-of-the-art Models 10%
• Support Vector Machine 10%
• SVM Model 10%
• Telecommunications 10%
• Telecommunications Industry 10%

Computer Science

• Classification Performance 14%
• Comparative Analysis 14%
• Decision Tree Learner 14%
• Effective Solution 14%
• Evaluation Metric 14%
• Gradient Boosting 100%
• Learning Process 14%
• Metaheuristics 100%
• Modified Version 14%
• Open Source 14%
• Particle Swarm Optimization 28%
• Prediction Model 100%
• Quantitative Evaluation 14%
• Radial Basis Function 14%
• Robust Solution 14%
• Support Vector Machine 14%
• Support Vector Machine 14%