A Self-Organizing Map (SOM) is a type of artificial neural network used primarily for unsupervised learning and data visualization. Developed by Teuvo Kohonen in the 1980s, SOMs are particularly effective for clustering and analyzing high-dimensional data by mapping it into a lower-dimensional space, typically two dimensions. ### Key Characteristics of Self-Organizing Maps: 1. **Topology Preservation**: SOMs maintain the topological relationships in the input data.
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