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Self-organization and clustering algorithms
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Bezdek, James C. |
| Copyright Year | 1991 |
| Description | Kohonen's feature maps approach to clustering is often likened to the k or c-means clustering algorithms. Here, the author identifies some similarities and differences between the hard and fuzzy c-Means (HCM/FCM) or ISODATA algorithms and Kohonen's self-organizing approach. The author concludes that some differences are significant, but at the same time there may be some important unknown relationships between the two methodologies. Several avenues of research are proposed. |
| File Size | 842875 |
| Page Count | 16 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19910012470 |
| Archival Resource Key | ark:/13960/t6547mn2z |
| Language | English |
| Publisher Date | 1991-02-01 |
| Access Restriction | Open |
| Subject Keyword | Computer Programming And Software Cluster Analysis Theorems Analogies Classifications Algorithms Probability Theory Self Organizing Systems Clumps Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
