Similarity-Based Clustering: Recent Developments and Biomedical Applications

Similarity—based learning methods have a great potential as an intuitive and flexible toolbox for mining, visualization,and inspection of largedata sets. They combine simple and human—understandable principles, such as distance—based classification, prototypes, or Hebbian learning, with a large variety of different, problem—adapted design choices, such as a data—optimum topology, similarity measure, or learning mode. In medicine, biology, and medical bioinformatics, more and more data arise...