Clustering

This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.

Avainsanat: data partitioning, partitioning of data, data storage, gigabytes, terabytes, applied mathematics, data clustering, automatic classification, numerical taxonomy, botryology, typological analysis, data mining, cluster data, Clustering, Unsupervised Learning, Neural Networks, Hierarchical Clustering, Partitional Clustering, Dimension Reduction, Sequential Data Clustering, Cluster Validation