دوشنبه 16 اسفند 1395
نویسنده: Marian Christenson
Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw
� John Wiley & Sons, 1990 Collective Intelligence. Finding Groups in Data: An Introduction to Cluster Analysis. Knowledge Discovery and Data Mining (PAKDD. Finding Groups in Data: An Introduction to Cluster Analysis (Wiley. Publications on Spatial Database and Spatial Data Mining at UMN . There is a specific k-medoids clustering algorithm for large datasets. Audience The following groups will find this book a valuable tool and reference: applied statisticians; engineers and scientists using data analysis; researchers in pattern recognition, artificial intelligence, machine learning, and data mining; and applied mathematicians. Kogan J., Nicholas C., Teboulle M. Clustering Large and High Dimensional data. Rousseeuw (1990), "Finding Groups in Data: an Introduction to Cluster Analysis" , Wiley. First, Finding groups in data: an introduction to cluster analysis (1990, by Kaufman and Rousseeuw) discussed fuzzy and nonfuzzy clustering on equal footing. Instructors can also use it as a textbook for an introductory course in cluster analysis or as source material for a graduate-level introduction to data mining. The algorithm is called Clara in R, and is described in chapter 3 of Finding Groups in Data: An Introduction to Cluster Analysis. Complete code of six stand-alone Fortran programs for cluster analysis, described and illustrated in L.