Multi-SConES

Enlarged view: Logo of 2014 SIAM conference on Data Mining

Mahito Sugiyama, Chloe-Agathe Azencott, Dominik Grimm, Yoshinobu Kawahara and Karsten Borgwardt

Multi-Task Feature Selection on Multiple Networks via Maximum Flows

Summary

This is a multi-task version of SConES, that allows for network GWAS with more than one network and more than one phenotype. This method achieves multi-task feature selection coupled with multiple network regularizers using a maximum-flow algorithm.

Code

An R implementation of the method can be found in our GitHub repository external page here.

Publication

Please see the following paper for detailed information and refer it in your published research.

Multi-Task Feature Selection on Multiple Networks via Maximum Flows

Mahito Sugiyama, Chloé-Agathe Azencott, Dominik G. Grimm, Yoshinobu Kawahara and Karsten Borgwardt
Proceedings of the 2014 SIAM International Conference on Data Mining 2014, 199-207
external page Online  |  ETH Research Collection  |  Project page  |  external page GitHub  |  Supplement

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