Automated, Interpretable and Efficient ML Models for Real-World Lightpaths’ Quality of Transmission Estimation

Computer Science

• Deep Neural Network 100%
• lightpath 100%
• Machine Learning Model 100%
• Domain Adaptation 66%
• Neural Network 66%
• Feature Extraction 66%
• Feature Selection 66%
• Transfer Learning 66%
• Fiber Optic Networks 66%
• SHapley Additive exPlanation 66%
• Quality of Service 33%
• Learning Approach 33%
• Machine Learning Algorithm 33%
• Random Decision Forest 33%
• Interpretability 33%
• Classification Accuracy 33%
• Learning Framework 33%
• Decision-Making 33%
• Convolutional Neural Network 33%
• Computational Resource 33%
• Baseline Model 33%
• Network Environment 33%
• Production Network 33%

Keyphrases

• SHAP Method 33%
• Feature Augmentation 33%
• Correlation Alignment 33%
• Automated Feature Selection 33%
• Seamless Operation 33%