Ensemble-learning based neural networks for novelty detection in multi-class systems

Keyphrases

• Neural Network 100%
• Novelty Detection 100%
• Learning-based 100%
• Ensemble Learning 100%
• Multi-class System 100%
• Abnormal Data 40%
• Training Phase 40%
• Semi-supervised Learning 40%
• Neural Network Learning 40%
• Learning Systems 20%
• Machine Learning System 20%
• Data-centric 20%
• Complete Set 20%
• Monitoring Data 20%
• Information Security 20%
• Real-world Systems 20%
• Two-in-one 20%
• Process Monitoring 20%
• Multi-class Classification 20%
• Business Intelligence 20%
• Detection Model 20%
• Machine Learning Datasets 20%
• One-class Classification 20%
• Ensemble Model 20%
• UCI Machine Learning 20%
• Clinical Decision Support 20%
• Classification Criteria 20%
• Intelligence Process 20%
• Novel Activation Functions 20%

Computer Science

• Ensemble Learning 100%
• Neural Network 100%
• Training Phase 66%
• Semisupervised Learning 66%
• Learning System 66%
• Machine Learning 33%
• Business Intelligence 33%
• Class Classification 33%
• Information Security 33%
• Intelligence Process 33%
• Initial Assumption 33%
• clinical decision support 33%
• Multi Class Classification 33%
• Critical System 33%
• Activation Function 33%
• Classification Accuracy 33%
• Multiclass Classification 33%
• Process Monitoring 33%
• Machine Learning 33%

Chemical Engineering

• Learning System 100%
• Neural Network 100%
• Supervised Learning 50%
• Process Monitoring 25%