Neural Networks

Self Organising Maps

Projects high-dimensional data onto a grid while preserving which things are near which.

A grid of units competes for each input; the winner and its neighbours move toward it. Over many passes the grid arranges itself so that similar inputs land in neighbouring cells.

The result is a two-dimensional map you can actually look at, which makes it a useful exploratory tool for segmentation before committing to a clustering method.

Also in Neural Networks

Perceptron Backpropagation Feed Forward Hopfield Network Boltzmann Machine Deep Belief Network

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