Comparison of logistic regression, support vector machines, and deep learning classifiers for predicting memory encoding success using human intracranial EEG recordings

Medicine & Life Sciences

• Electrocorticography 100%
• Deep Learning 98%
• Support Vector Machine 87%
• Machine Learning 81%
• Memory 52%
• Logistic Models 47%
• Brain 35%
• Episodic Memory 23%
• Electroencephalography 17%
• Brain-Computer Interfaces 13%
• Implanted Electrodes 12%
• Equipment and Supplies 12%
• Area Under Curve 8%
• Datasets 8%

Engineering & Materials Science

• Logistic regression 79%
• Electroencephalography 68%
• Deep learning 63%
• Brain 59%
• Support vector machines 57%
• Machine learning 52%
• Classifiers 50%
• Data storage equipment 43%
• Dimensionality reduction 9%
• Interfaces (computer) 8%
• Frequency bands 7%
• Electrodes 6%
• Testing 4%