Projection-Based Clustering through Self-Organization and Swarm Intelligence: Combining Cluster Analysis with the Visualization of High-Dimensional Data

• Main Author: Michael Christoph Thrun (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: Springer Nature 2018
• Subjects: Visualization; Knowledge Discovery; Swarm Intelligence; Unsupervised Machine Learning; Data Science; Game Theory; 3D Printing; Dimensionality Reduction; Multivariate Data; Analysis of Structured Data; Self-Organization; Emergence; Advanced Analytics; High-Dimensional Data; Cluster Analysis
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.