Projection-Based Clustering Through Self-Organization and Swarm Intelligence: Combining Cluster Analysis With the Visualization of High-Dimensional Da (Paperback or Softback)

Michael Christoph Thrun

ISBN 10: 101326990X / ISBN 13: 9781013269905

Published by Saint Philip Street Press 10/8/2020, 2020

About this Item

Projection-Based Clustering Through Self-Organization and Swarm Intelligence: Combining Cluster Analysis With the Visualization of High-Dimensional Da 1.11.

Seller Inventory # BBS-9781013269905

Bibliographic Details

• Title: Projection-Based Clustering Through Self-Organization and Swarm Intelligence: Combining Cluster Analysis With the Visualization of High-Dimensional Da (Paperback or Softback)
• Publisher: Saint Philip Street Press 10/8/2020
• Publication Date: 2020
• Language: English
• ISBN 10: 101326990X
• ISBN 13: 9781013269905
• Binding: Paperback or Softback
• Condition: New
• Book Type: Book

About this title

Synopsis

This book covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm (DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures.The clustering and number of clusters or an absence of cluster structure are verified by the 3D landscape at a glance. DBS is the first swarm-based technique that shows emergent properties while exploiting concepts of swarm intelligence, self-organization and the Nash equilibrium concept from game theory. It results in the elimination of a global objective function and the setting of parameters. By downloading the R package DBS can be applied to data drawn from diverse research fields and used even by non-professionals in the field of data mining.

This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.