The Self-Organizing Map (SOM), commonly also known as Kohonen network (Kohonen 1982, Kohonen 2001) is a computational method for the visualization and analysis of high-dimensional data, especially experimentally acquired information.
Extracted from scholarpedia
Sources:
Image: scholarpedia
Book: Self-Organizing Maps
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Clustering | 21 | 16.54% |
Quantization | 10 | 7.87% |
General Classification | 10 | 7.87% |
Classification | 6 | 4.72% |
Time Series Analysis | 6 | 4.72% |
Dimensionality Reduction | 5 | 3.94% |
Image Classification | 4 | 3.15% |
BIG-bench Machine Learning | 4 | 3.15% |
Continual Learning | 2 | 1.57% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |