Publication:
Projection-Based Clustering through Self-Organization and Swarm Intelligence
Projection-Based Clustering through Self-Organization and Swarm Intelligence
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Date
2018
Authors
Michael Christoph Thrun
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Research Projects
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Abstract
This open access 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.
Description
DOI: https://doi.org/10.1007/978-3-658-20540-9; License: CC BY; Publisher: Springer
Keywords
Open Access,
Cluster Analysis,
Dimensionality Reduction,
Swarm Intelligence,
Visualization,
Unsupervised machine learning,
Data science,
Knowledge Discovery,
3D printing,
Self-Organization,
Emergence,
Game theory,
Advanced Analytics,
High-dimensional data,
Multivariate data,
Analysis of stuctured data,
data structures