A novel intelligent system for detection of Type 2 Diabetes with modified loss function and regularization

Computer Science

• Deep Learning Model 100%
• Regularization 100%
• Machine Learning 100%
• Learning System 100%
• Continuous Monitoring 50%
• Neural Network Model 50%
• Random Decision Forest 50%
• Majority Voting 50%
• Deep Neural Network 50%
• Regularization Function 50%
• Support Vector Machine 50%
• Processing Time 50%
• Early Detection 50%
• Logistic Regression 50%
• Machine Learning Model 50%

Keyphrases

• Type 2 Diabetes Mellitus (T2DM) 100%
• Intelligent Systems 100%
• Modified Loss Function 100%
• Loss of Regularity 100%
• Model Solution 33%
• Deep Learning Model 33%
• Machine Learning Learning 33%
• Ensemble Model 33%
• Deep Machine Learning 33%
• Prediction Accuracy 16%
• Diabetes 16%
• Early Detection 16%
• Logistic Regression 16%
• Processing Time 16%
• High Diversity 16%
• Machine Learning Models 16%
• Prediction Skill 16%
• Diabetes Prevalence 16%
• Continuous Monitoring 16%
• Single Model 16%
• Overfitting 16%
• Majority Voting Technique 16%
• Regularization Method 16%
• Deep Neural Network 16%
• Regression Forest 16%
• Generalization Ability 16%
• SVM Neural Network 16%
• Pima Indians 16%
• Random Forest Neural Networks 16%
• Diabetes Dataset 16%
• Enhanced Systems 16%

Mathematics

• Regularization 100%
• Loss Function 100%
• Ensemble Model 66%
• Deep Learning Method 66%
• Logistic Regression 33%
• Deep Neural Network 33%
• Network Model 33%
• Accurate Prediction 33%