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Projection-Based Clustering through Self-Organization and Swarm Intelligence
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-d...
সংরক্ষণ করুন:
| প্রধান লেখক: | |
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| অন্যান্য লেখক: | |
| বিন্যাস: | Dissertation |
| ভাষা: | ইংরেজি |
| প্রকাশিত: |
Philipps-Universität Marburg
2018
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | পিডিএফ এ সম্পূর্ন পাঠ |
| ট্যাগগুলো: |
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| সংক্ষিপ্ত: | 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. |
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| দৈহিক বর্ননা: | 210 Seiten |
| আইসবিএন: | 978-3-658-20540-9 |
| ডিওআই: | 10.17192/es2018.0002 |