By Ronald S. King
+ areas emphasis on illustrating the underlying common sense in making judgements throughout the cluster research
+Discusses the similar purposes of statistic, e.g., Ward’s procedure (ANOVA), JAN (regression research & correlational analysis),
cluster validation (hypothesis checking out, goodness-of-fit, Monte Carlo simulation, etc.)
+ includes separate chapters on JAN and the clustering of express data
+ encompasses a significant other disc with ideas to routines, courses, facts units, charts, etc.[Note:The better half disc documents can be found with Amazon facts of buy from firstname.lastname@example.org.]
Brief desk of Contents
1: creation to Cluster research. 2: assessment of information Mining. three: Hierarchical Clustering . four: Partition Clustering. five: Judgmental research. 6: Fuzzy Clustering types and purposes. 7: type and organization principles. eight: Cluster Validity. nine: Clustering express facts. 10: Mining Outliers. eleven: Model-based Clustering. 12: normal concerns. Appendices. Index.
On the better half Disc!
[Note:The significant other disc records can be found with Amazon evidence of buy from email@example.com.]
Appendix A: Clustering research with SPSS
Appendix B: Clustering research with SAS
Appendix C: Neymann-Scott Cluster Generator software Listing
Appendix D: Jancey’s Clustering software Listing
Appendix E: JAN Program
Appendix F: UCI computing device studying Depository KD Nuggets information Sets
Appendix G: unfastened facts software program (Calculator)
Appendix H: options to extraordinary Exercises
About the Author
Ronald S. King holds a PhD in utilized information and presently teaches on-line classes for Tarleton nation college (TX). Spanning a occupation of 4 many years of educating and management at a number of universities, he brings a distinct viewpoint to the fields of records, laptop technological know-how, and data structures. His lifetime profession courses have made a number of contributions to those fields.
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Extra info for Cluster Analysis and Data Mining: An Introduction
Cluster Analysis and Data Mining: An Introduction by Ronald S. King