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Projection-Based Clustering through Self-Organization and Swarm Intelligence = Combining Cluster Analysis with the Visualization of High-Dimensional Data /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Projection-Based Clustering through Self-Organization and Swarm Intelligence/ by Michael Christoph Thrun.
其他題名:
Combining Cluster Analysis with the Visualization of High-Dimensional Data /
作者:
Thrun, Michael Christoph.
面頁冊數:
XX, 201 p. 90 illus., 29 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Pattern recognition. -
電子資源:
https://doi.org/10.1007/978-3-658-20540-9
ISBN:
9783658205409
Projection-Based Clustering through Self-Organization and Swarm Intelligence = Combining Cluster Analysis with the Visualization of High-Dimensional Data /
Thrun, Michael Christoph.
Projection-Based Clustering through Self-Organization and Swarm Intelligence
Combining Cluster Analysis with the Visualization of High-Dimensional Data /[electronic resource] :by Michael Christoph Thrun. - 1st ed. 2018. - XX, 201 p. 90 illus., 29 illus. in color.online resource.
Approaches to Unsupervised Machine Learning -- Methods of Visualization of High-Dimensional Data -- Quality Assessments of Visualizations -- Behavior-Based Systems in Data Science -- Databionic Swarm (DBS).
Open Access
This book is published open access under a CC BY 4.0 license. It 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. Contents Approaches to Unsupervised Machine Learning Methods of Visualization of High-Dimensional Data Quality Assessments of Visualizations Behavior-Based Systems in Data Science Databionic Swarm (DBS) Target Groups Lecturers, students as well as non-professional users of data science, statistics, computer science, business mathematics, medicine, biology The Author Michael C. Thrun, Dipl.-Phys., successfully defended his Ph.D. in 2017 at the Philipps University of Marburg. Thrun’s advisor was the Chair of Neuroinformatics, Prof. Dr. rer. nat. Alfred G. H. Ultsch.
ISBN: 9783658205409
Standard No.: 10.1007/978-3-658-20540-9doiSubjects--Topical Terms:
1253525
Pattern recognition.
LC Class. No.: Q337.5
Dewey Class. No.: 006.4
Projection-Based Clustering through Self-Organization and Swarm Intelligence = Combining Cluster Analysis with the Visualization of High-Dimensional Data /
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