Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.The

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.

Karlsson has assembled a strong mix of papers that collectively provide a good sense of some of the latest research in the field. Edward Feser, Review of Regional Studies This is a book every regional scientist and spatial analyst should have on their bookshelf. Like most Handbook type publications it provides depth and breadth on the basics of the industrial clustering concept. However, unlike most of these type of collections, it goes beyond the foundation material to identify and speculate on questions that are emerging on the research frontiers such as at the intersection of cluster theory and agglomeration processes, knowledge spillovers and technology transfer not to mention the obvious link to economic development theory, policy and practice. Roger R. Stough, George Mason University, US This eclectic volume presents a host of methods to describe tendencies for the joint location of economic agents in space. And it illustrates useful applications of these concepts in diverse fields financial services, culture, tourism, and industry, to name just a few. John M. Quigley, University of California, US Clusters have increasingly dominated local and regional development policies in recent decades and the growing intellectual and political interest for clusters and clustering is the prime motivation for this Handbook. Charlie Karlsson unites leading experts to present a thorough overview of economic cluster research. Topics explored include agglomeration and cluster theory, methods for analysing clusters, clustering in different spatial contexts and clustering in service industries. Encompassing the developed economies of Europe and North America, the Handbook provides a basis for improving cluster policy formulation, interpretation and analyses. This comprehensive overview of research on economic clusters will be of interest to scholars and PhD students in (regional) economics, economic geography, regional planning and management as well as practitioners and policymakers at the national, regional and local levels involved in cluster formation and cluster management.

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Although clustering--the classification of objects into meaningful sets--is an important procedure in the social sciences today, cluster analysis as a multivariate statistical procedure is poorly understood by many social scientists. This volume is an introduction to cluster analysis for social scientists and students.