K Means Matlab
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Advances in K-means Clustering
Author: Junjie Wu
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-07-09
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" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.
Constrained Clustering
This volume encompasses many new types of constraints and clustering methods as well as delivers thorough coverage of the capabilities and limitations of constrained clustering. With contributions from industrial researchers and leading academic experts who pioneered the field, it provides a well-balanced combination of theoretical advances, key algorithmic development, and novel applications. The book presents various types of constraints for clustering and describes useful variations of the standard problem of clustering under constraints. It also demonstrates the application of clustering with constraints to relational, bibliographic, and video data.
Human Centered Computing
This book constitutes thoroughly reviewed, revised and selected papers from the 4th International Conference on Human Centered Computing, HCC 2018, held in Merida, Mexico, in December 2018. The 50 full and 18 short papers presented in this volume were carefully reviewed and selected from a total of 146 submissions. They focus on a "hyper-connected world", dealing with new developments in artificial intelligence, deep learning, brain-computing, etc.