# Incremental grid growing: encoding high-dimensional structure into a two-dimensional feature map

@article{Blackmore1993IncrementalGG, title={Incremental grid growing: encoding high-dimensional structure into a two-dimensional feature map}, author={Justine Blackmore and Risto Miikkulainen}, journal={IEEE International Conference on Neural Networks}, year={1993}, pages={450-455 vol.1} }

Ordinary feature maps with fully connected, fixed grid topology cannot properly reflect the structure of clusters in the input space. Incremental feature map algorithms, where nodes and connections are added to or deleted from the map according to the input distribution can overcome this problem. Such algorithms have been limited to maps that can be drawn in 2-D only in the case of two-dimensional input space. In the proposed approach, nodes are added incrementally to a regular two-dimensional…

## 151 Citations

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The Growing Hierarchical Self-Organizing Map (GH-SOM), a neural network model based on the self-organizing map, which has the capability of growing both in terms of map size as well as in a three-dimensional tree-structure in order to represent the hierarchical structure present in a data collection.

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