Zhu, Xibin: Adaptive prototype-based dissimilarity learning. 2015
Inhalt
- Introduction
- Prototype-based learning
- Introduction
- Prototype-based clustering
- Prototype-based classification
- Advantages of prototype-based methods
- Evaluation measures
- Conclusions
- Challenges of dissimilarity data
- Introduction
- Properties of dissimilarity data
- Linear embedding of dissimilarity data
- Ways to deal with dissimilarity data
- Data sets
- Conclusions
- Prototype-based learning for dissimilarity data
- Introduction
- A Review: relational prototype-based clustering
- Relational prototype-based classification
- Experiments
- Conclusions
- Speed-up techniques for large scale problems
- Introduction
- Patch processing
- Nyström approximation
- Experiments on biomedical applications
- Patch and Nyström RGLVQ
- Conclusions
- Adaptive conformal learning vector quantization
- Introduction
- Conformal prediction
- Prediction region and non-conformity measure
- Confidence and credibility
- Inductive conformal prediction
- Validity of conformal predictors
- Adaptive conformal relational GLVQ
- Experiments
- Conclusions
- Adaptive conformal semi-supervised LVQ
- Conclusions
- Bibliography