What is SOM?

A Self-Organizing Map (SOM) is a type of unsupervised learning, artificial neural network that produces a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map. SOMs are used for dimensionality reduction, feature extraction, clustering, and visualization of high-dimensional data. They are commonly used in areas like pattern recognition, image processing, and data analysis to discover relationships and patterns in complex datasets.