Clustering Stability: An Overview provides a high-level overview about the existing literature on clustering stability. It reviews different protocols for how clustering stability is computed and used for model selection. The main body of the text goes on to examine theoretical results for the K-means algorithm and discuss their various relations. Finally, it looks at results for more general clustering algorithms. In addition to presenting the results in a slightly informal but accessible way, Clustering Stability: An Overview relates them to each other and discusses their different implications.
1: Introduction 2: Clustering stability: definition and implementation 3: Stability analysis of the K-means algorithm 4: Beyond K-means 5: Outlook. References.
Series: Foundations and Trends(r) in Machine Learning
Number Of Pages: 54
Published: 29th March 2010
Country of Publication: US
Dimensions (cm): 23.39 x 15.6
Weight (kg): 0.09