TY - BOOK ID - 32076608 TI - Projection-Based Clustering through Self-Organization and Swarm Intelligence : Combining Cluster Analysis with the Visualization of High-Dimensional Data PY - 2018 SN - 3658205407 3658205393 PB - Cham Springer Nature DB - UniCat KW - Computer science. KW - Data structures (Computer science). KW - Pattern recognition. KW - Computer Science. KW - Pattern Recognition. KW - Data Structures. KW - Design perception KW - Pattern recognition KW - Form perception KW - Perception KW - Figure-ground perception KW - Information structures (Computer science) KW - Structures, Data (Computer science) KW - Structures, Information (Computer science) KW - Electronic data processing KW - File organization (Computer science) KW - Abstract data types (Computer science) KW - Informatics KW - Science KW - Optical pattern recognition. KW - Data structures (Computer scienc. KW - Optical data processing KW - Pattern perception KW - Perceptrons KW - Visual discrimination KW - Data structures (Computer science) KW - Cluster Analysis KW - Dimensionality Reduction KW - Swarm Intelligence KW - Visualization KW - Unsupervised Machine Learning KW - Data Science KW - Knowledge Discovery KW - 3D Printing KW - Self-Organization KW - Emergence KW - Game Theory KW - Advanced Analytics KW - High-Dimensional Data KW - Multivariate Data KW - Analysis of Structured Data UR - https://www.unicat.be/uniCat?func=search&query=sysid:32076608 AB - 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. ER -