Tool/Resource: GraphVar: A user-friendly toolbox for comprehensive graph analyses of functional brain connectivity - News

Fix for GraphVar 2: Hyperparamter

johndkk@stage.nitrcce.org (Johann Kruschwitz) — Mon, 19 Nov 2018 10:31:34 GMT

fixed an issue for LinSVM (classification, regression, probabilisitc): tuned hyperparameters derived from nested-cross validation
were not applied to the models (i.e., prediction was similar to no hyperparameter optimization). ElasticNet was unaffected.

GraphVar 2.0 machine learning paper in JNeuroscience Methods

johndkk@stage.nitrcce.org (Johann Kruschwitz) — Wed, 18 Jul 2018 11:00:23 GMT

Our second GraphVar article (accompanying the GraphVar 2.0 toolbox) is published in the Journal of Neuroscience Methods.
The article provides an easy to follow introductory review to the basics of machine learning and its application within GraphVar. GraphVar 2.0 will make big data neuroscience readily accessible to a broader audience of neuroimaging investigators.

https://doi.org/10.1016/j.jneumeth.2018.07.001

GraphVar now published in "Journal of Neuroscience Methods"

johndkk@stage.nitrcce.org (Johann Kruschwitz) — Thu, 26 Feb 2015 14:15:18 GMT

The GraphVar Team is happy to announce that GraphVar (https://www.nitrc.org/projects/graphvar/) is now published in the "Journal of Neuroscience Methods"!

If you think that GraphVar is useful for your work we would be happy if you cite this toolbox as:

Kruschwitz JD, List D, Waller L, Rubinov M, Walter H, GraphVar: A user-friendly toolbox for comprehensive graph analyses of functional brain connectivity, Journal of Neuroscience Methods (2015), http://dx.doi.org/10.1016/j.jneumeth.2015.02.021