A machine learning-based credit risk prediction engine system using a stacked classifier and a filter-based feature selection method

Computer Science

• Artificial Neural Network 33%
• Computing Power 33%
• Decision Trees 33%
• Experimental Result 33%
• Extreme Gradient Boosting 33%
• Feature Selection 100%
• Gradient Boosting 33%
• Information Gain 33%
• Machine Learning 100%
• Prediction Model 33%
• Random Decision Forest 33%

Keyphrases

• Credit Risk Prediction 100%
• Data Power 25%
• Following Methods 25%
• Multiple Datasets 25%
• Prediction Engine 100%
• Risk Prediction Model 25%
• Stacked Architecture 25%
• Stacking Classifier 100%