Cluster analysis is used in data mining and is a common technique for statistical data analysis used in many fields of study, such as the medical & life sciences, behavioral & social sciences, engineering, and in computer science. This book is applicable to either a course on clustering and classification or as a companion text for a first class in applied statistics.
- Puts emphasis on illustrating the underlying logic in making decisions during the cluster analysis
- Brings out the related applications of statistics: Ward’s method (ANOVA), JAN (regression analysis & correlational analysis), cluster validation (hypothesis testing, goodness-of-fit, Monte Carlo simulation, etc.)
- Includes separate chapters on JAN and the clustering of categorical data
BRIEF TABLE OF CONTENTS
1: Introduction to Cluster Analysis. 2: Overview of Data Mining. 3: Hierarchical Clustering. 4: Partition Clustering. 5: Judgmental Analysis. 6: Fuzzy Clustering Models and Applications. 7: Classification and Association Rules. 8: Cluster Validity. 9: Clustering Categorical Data. 10: Mining Outliers. 11: Model-based Clustering. 12: General Issues. Appendices.
AUTOR: Ronald S. King
EDITORA: Mercury Learning & Information
EDIÇÃO: 1ª / 2014
DISPONIBILIDADE DO PRODUTO: Sob Encomenda - 40 dias ( Importação )