Feature Extraction and Classification using Leading Eigenvectors: Applications in Biomedical and Multi-Modal mHealth Data

Engineering

• Feature Extraction 100%
• Experiments 60%
• Dataset 60%
• Demonstrates 20%
• Supports 20%
• Models 20%
• Reduction 20%
• Computational Complexity 20%
• Learning Task 20%
• Singular Value Decomposition 20%
• Large Multi 20%

Computer Science

• Feature Extraction 100%
• Classifier 80%
• Approximation (Algorithm) 40%
• Accuracy 20%
• Computational Complexity 20%
• Singular Value 20%
• Machine Learning 20%
• Kernel Method 20%
• Factorization 20%
• Deep Learning Model 20%