Data Visualization Method for Growing Self-Organizing Networks with Ant Clustering Algorithm

The growing self-organizing networks are useful tools suitable for data analysis in which networks learn the topology of the high-dimensional data by inserting/deleting neurons. However, these methods cannot represent the high-dimensional clusters on the lower-dimensional intuitive space. In this paper, we proposed the visualization method by ant clustering to construct the two-dimensional feature map for the growing self-organizing networks.