title: Clustering criteria and algorithms.
abstract: Cluster analysis is an unsupervised pattern recognition frequently used in biology, where large amounts of data must often be classified. Hierarchical agglomerative approaches, the most commonly used techniques in biology, are described in this chapter. Particular attention is put on techniques for validating the optimal cluster number and the clustering quality.
authors.affiliation: Department of General Chemistry, Pavia University, Pavia, Italy.
authors.forename: Oliviero
authors.initials: O
authors.lastname: Carugo
mesh_terms: D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D057225:Data Mining; D019992:Databases as Topic; D006801:Humans; D020407:Internet; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D049490:Systems Biology; D018511:Systems Integration