Randomized nonlinear one-class support vector machines with bounded loss function to detect of outliers for large scale IoT data

Keyphrases

• Anomaly Detection 100%
• One-class Support Vector Machine (OCSVM) 100%
• IoT Data 100%
• Bounded Loss Function 100%
• Massive IoT 100%
• Large-scale Data 66%
• Nonlinear Features 66%
• Copyright 33%
• Challenging Tasks 33%
• Breast Cancer 33%
• Exponential Growth 33%
• Hepatitis 33%
• Benchmark Dataset 33%
• Data Acquisition System 33%
• Support Vector Machine 33%
• High-dimensional Data 33%
• Blood Transfusion 33%
• Computational Complexity 33%
• Industrial Internet of Things (IIoT) 33%
• Support Vector 33%
• Parkinson 33%
• Optimized Support 33%
• Maximum Margin 33%
• Optimal Hyperplane 33%
• Unusual Patterns 33%
• Gas Sensor Array 33%
• Unbounded Loss Function 33%
• Large Loss 33%
• Human Activity Recognition 33%
• Hinge Loss 33%

Engineering

• Support Vector Machine 100%
• Loss Function 100%
• Internet of Things 100%
• Anomaly Detection 75%
• Nonlinear Feature 50%
• Tasks 25%
• Exponential Growth 25%
• Computational Complexity 25%
• Sensor Array 25%
• Dimensional Data 25%
• Industrial Internet 25%
• Data Acquisition Device 25%
• Hyperplanes 25%
• Gas Sensor 25%
• Computational Space 25%

Computer Science

• Internet of Things 100%
• Support Vector Machine 100%
• Anomaly Detection 75%
• Large Scale Data 50%
• Computational Complexity 25%
• Large Data Set 25%
• Space Complexity 25%
• High Dimensional Data 25%
• Industrial Internet of Things 25%
• Support Vector 25%
• Exponential Growth 25%
• Human Activity Recognition 25%
• Hyperplanes 25%