Emotion on the edge: an evaluation of feature representations and machine learning models

Computer Science

• Inverse Document Frequency 100%
• Machine Learning Model 100%
• Performance Model 66%
• DistilBERT 66%
• Classification Models 33%
• Support Vector Machine 33%
• Machine Learning 33%
• Learning System 33%
• Frequency Feature 33%
• Influence Model 33%
• Transformer Model 33%
• Stochastic Gradient Descent 33%

Keyphrases

• Frequency Model 66%
• Affect Model 33%
• Low Computation Power 33%
• Edge Board 33%
• Textual Emotion Classification 33%