Self-organizing Network

This toolbox includes codes and the example of Self-organizing network for variable clustering.

This toolbox includes codes and the example of Self-organizing variable clustering. Each variable is represented as a node in the complex network. Nonlinear-coupling forces move these nodes to derive a self-organizing topology of the network. As such, variables are clustered into sub-network communities.

The demo codes simulate and generate two clusters of variables, then demonstrate the codes with the measure of variable-to-variable pairwise distances. This measure can be replaced with the use of nonlinear coupling analysis to characterize and qualtify variable-to-variable interdependence structures (see Ref[2] for group variable selection).

Author: Dr. Hui Yang

Affiliation:

The Pennsylvania State University

310 Leohard Building, University Park, PA

Email: [e-mail]

If you find this toolbox useful, please cite the following paper:

[1] H. Yang and G. Liu, “Self-organized topology of recurrence-based complex networks,” Chaos, Vol. 23, No. 4, p. 043116, 2013, DOI: 10.1063/1.4829877G.

[2] Liu and H. Yang, "Self-organizing network for group variable selection and predictive modeling,” Annals of Operations Research, Vol. 263, No. 1, p. 119-140, 2017. DOI: 10.1007/s10479-017-2442-2

https://youtu.be/BwgjK8t7Pso?si=pNBckLuAgGf1Q_-K