The cross-validated AUC for MCP-logistic regression with high-dimensional data

Mathematics

• Bayesian Information Criterion 100%
• Minimax 66%
• Akaike Information Criterion 66%
• Logistic Regression 50%
• Selection 50%
• Parameters 50%
• Logistic Regression Model 33%
• Simulation Study 33%
• Classification 33%
• Characteristic Curve 16%
• Penalty Method 16%
• Dimensional Data 16%
• Algorithm 16%
• Variables 16%
• Samples 16%
• Operators 16%

Economics, Econometrics and Finance

• Logit Model 83%
• Regression Model 33%

Food Science

• Microarray 16%