Bio-sensor based on multiclass support vector machine with a reject option

Keyphrases

• Sampling numbers 100%
• Overall Accuracy 100%
• One-class Support Vector Machine (OCSVM) 100%
• Sensor-based 100%
• Reject Option 100%
• Glucose Level 50%
• Patients with Diabetes Mellitus 50%
• Real-world Problems 50%
• Low Dose Rate 50%
• Prediction Accuracy 50%
• Multi-class Classification 50%
• Remote Sensing 50%
• Abstaining 50%
• Photonics 50%
• Cost Function 50%
• Multi-class 50%
• Rejection Rate 50%
• Support Vector Machine 50%
• Labeled Sample 50%
• Thentest 50%
• Training Algorithm 50%
• Non-invasive Way 50%
• Machine Structure 50%
• Posterior Probability 50%
• Biomedical Parameters 50%
• High Rejection 50%
• Derivates 50%
• Classification Process 50%
• Rejection Cost 50%
• Bayes Rule 50%
• General Training 50%
• Sensing Field 50%
• Misprediction 50%
• Surrogate Loss 50%
• Medical Sensing 50%
• Surrogate Loss Function 50%

Engineering

• Support Vector Machine 100%
• Biosensor 100%
• Decision Rule 100%
• Photonics 33%
• Posterior Probability 33%
• Real Life 33%
• Cost Function 33%
• Multiclass Classification 33%
• Loss Function 33%
• Classification Process 33%
• Machine Structure 33%

Computer Science

• Support Vector Machine 100%
• training algorithm 50%
• Multiclass Classification 50%
• Posterior Probability 50%
• Classification Process 50%
• Bayes Decision Rule 50%