Cluster Analysis and Data Mining: An Introduction

Cluster Analysis and Data Mining: An Introduction
  • eBook:
    Cluster Analysis and Data Mining: An Introduction
  • Author:
    Ronald S. King
  • Edition:
  • Categories:
  • Data:
    November 21, 2014
  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
    300 pages
  • Format:
    PDF, ePUB

Book Description
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. Designed for training industry professionals or for a course on clustering and classification, it can also be used as a companion text for applied statistics. No previous experience in clustering or data mining is assumed. Informal algorithms for clustering data and interpreting results are emphasized. In order to evaluate the results of clustering and to explore data, graphical methods and data structures are used for representing data. Throughout the text, examples and references are provided, in order to enable the material to be comprehensible for a diverse audience. A companion disc includes numerous appendices with programs, data, charts, solutions, etc.


Chapter 1: Introduction to Cluster Analysis
Chapter 2: Overview of Data Mining
Chapter 3: Hierarchical Clustering
Chapter 4: Partition Clustering
Chapter 5: Judgmental Analysis
Chapter 6: Fuzzy Clustering Models and Applications
Chapter 7: Classification and Association Rules
Chapter 8: Cluster Validity
Chapter 9: Clustering Categorical Data
Chapter 10: Mining Outliers
Chapter 11: Model-based Clustering
Chapter 12: General Issues

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