Cross-validation of correlation networks using modular structure

Cross-validation of correlation networks using modular structure

Abstract Correlation networks derived from multivariate data appear in many applications across the sciences. These networks are usually dense and require sparsification to detect meaningful structure. However, current methods for sparsifying correlation networks struggle with balancing overfitting...

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Bibliographic Details
Main Authors: Magnus Neuman, Viktor Jonsson, Joaquín Calatayud, Martin Rosvall
Format: Article
Language:English
Published: SpringerOpen 2022-11-01
Series:Applied Network Science
Subjects:
Correlation networks
Modular structure
Cross-validation
Information theory
Gene co-expression
Online Access:https://doi.org/10.1007/s41109-022-00516-5

Internet

https://doi.org/10.1007/s41109-022-00516-5

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