Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions

Engineering

• Feature Extraction 100%
• Random Forest 66%
• Computational Efficiency 66%
• Input Feature 66%
• Least Absolute Shrinkage and Selection Operator 66%
• Prediction Error 66%
• Learning System 66%
• Porosity 66%
• Dimensionality 33%
• Regressors 33%
• Regularization Method 33%
• Regularization 33%
• Data Preprocessing 33%

Computer Science

• Feature Selection 100%
• Gradient Boosting 100%
• Feature Extraction 100%
• Random Decision Forest 66%
• Computational Efficiency 66%
• Prediction Error 66%
• Preprocessing Step 33%
• Data Preprocessing 33%
• Regularization 33%
• Machine Learning 33%
• Learning System 33%
• Machine Learning Model 33%
• Regularization Method 33%

Earth and Planetary Sciences

• Reservoir Characterization 100%
• Porosity 100%
• Computational Efficiency 100%
• Machine Learning 50%
• Machine Learning Model 50%