Self-Organizing Map

Self-Organizing Maps (SOMs) are a form of artificial neural networks designed to transform and visualize complex data structures. They use a competitive learning process, where neurons compete to become activated by input data, effectively clustering similar data points in a two-dimensional space. This technique is particularly useful for discovering patterns and relationships in large datasets without prior labeling.