Articles for tag: competitive learning, data This, high-dimensional data, input data, Organizing Maps, Self Organizing

Exploring Self Organizing Maps: A Guide to Understanding and Implementing This Powerful Neural Network

Self Organizing Maps (SOMs) are a type of unsupervised neural network that can be used for data visualization, pattern recognition, and clustering. With their unique topology and adaptive learning algorithm, SOMs are able to represent high-dimensional data in a lower-dimensional grid-like structure, making them an ideal tool for exploring complex datasets. Unlike traditional neural networks, ...