A novel multi-relation regularization method for regression and classification in AD diagnosis

Keyphrases

• Regularization Method 100%
• AD Diagnosis 100%
• Multi-relation 100%
• Feature Selection 66%
• L1-norm 66%
• Alzheimer's Disease Diagnosis 33%
• Alzheimer's Disease Neuroimaging Initiative 33%
• Correlation Coefficient 33%
• State-of-the-art Techniques 33%
• Clinical Score 33%
• Least Squares Support Vector Regression (LSSVR) 33%
• Classification Accuracy 33%
• Disease Status 33%
• Root Mean Square Error 33%
• Classification Model 33%
• Area under the Receiver Operating Characteristic Curve 33%
• Mini-Mental State Examination 33%
• Sensitivity Specificity 33%
• Support Vector Classification 33%
• Response Relationship 33%
• Sensitivity Area 33%
• Weight Coefficient 33%
• Alzheimer's Disease Assessment Scale-Cognitive Subscale 33%
• Status Identification 33%
• Relational Information 33%
• Joint Regression 33%
• Clinical Prediction Score 33%
• Joint Classification 33%
• Relationship Characteristics 33%
• Relational Features 33%
• Feature Relation 33%
• Least Squares Regression 33%
• Optimal Weight Coefficient 33%

Computer Science

• Regularization Method 100%
• Feature Selection 66%
• Feature Extraction 66%
• Experimental Result 33%
• Support Vector 33%
• Least Squares Method 33%
• Support Vector Regression 33%
• Classification Accuracy 33%
• Classification Models 33%
• Objective Function 33%
• Characteristic Curve 33%
• Root Mean Squared Error 33%

Mathematics

• Regularization 100%
• Support Vector Machine 66%
• Objective Function 33%
• Disease Status 33%
• correlation coefficient ρ 33%
• Least Square 33%
• Regression Model 33%
• Squared Error 33%
• Characteristic Curve 33%
• Square Regression 33%