Question

Write a detail note on self organizing map

Answer 1

A self-organizing map (SOM) is a type of artificial neural network that uses unsupervised learning to build a two-dimensional map of a problem space. They are also known as a self-organizing feature map (SOFM) or a Kohonen map. It belongs to the category of competitive learning networks. The Self-Organizing Map is based on unsupervised learning, which means that no human intervention is needed during the learning and that little needs to be known about the characteristics of the input data.

A self-organizing map can generate a visual representation of data on a hexagonal or rectangular grid. Applications include meteorology, oceanography, project prioritization, and oil and gas exploration.

The Self organising map algorithm is based on unsupervised, competitive learning. It provides a topology preserving mapping from the high dimensional space to map units. Map units, or neurons, usually form a two-dimensional lattice and thus the mapping is a mapping from high dimensional space onto a plane.

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