Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen almost through trial and error. Even the two most popular, an
This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techn
This book presents the most recent advances in fuzzy clustering techniques and their applications. The contents include Introduction to Fuzzy Clustering; Fuzzy Clustering based Principal Component Ana
"This book examines the development and role of small business clusters from a variety of disciplines : economics, marketing, management and information systems. It gathers perspectives from varied di
The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as fo
A central principle in the design of large-scale distributed systems is that components should be organized to place those that interact frequently close together. This is essentially a basic clusteri
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old"
This book offers a systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended result
Es handelt sich um eine Anthologie von ca. 110 Gedichten mit Bezug zur Mathematik (teilweise auch Physik). Sie gliedert sich in 5 Teile, jedes einem bestimmten Thema gewidmet. Unter den Autoren finde
This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partiti
Cluster Analysis is an important tool in a variety of scientific areas. Chapter 1 briefly presents a state of the art of already well-established as well more recent methods. The hierarchical, partiti
Cluster analysis means the organization of an unlabeled collection of objects or patterns into separate groups based on their similarity. The task of computerized data clustering has been approached f
This book deals with the methods of text comparison which are based on different techniques of converting the text into a distribution on a certain finite support, be it a genetic text or a text of so
This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in par
Explore clustering algorithms used with Apache MahoutAbout This BookUse Mahout for clustering datasets and gain useful insightsExplore the different clustering algorithms used in day-to-day workA prac
