Dear fellow ROOT-ers and TMVA-users,
I am using the TMVA package to perform a classification problem and in particular, have been focusing on the various neural-net based methods to try and accomplish this.
Poking around the internet, I have heard several mentions of features that are not present in the TMVA users’ guide [1], such as “deep”-neural networks (DNN [2]), and additional cross-validation techniques besides the default train/test split (e.g. mentions of k-fold cross validation). Now, granted, the users’ guide is somewhat old (at least, the first version I find with a simple google search), but I do see in later ROOT versions (6.x.y onwards it seems) that there is the existence of “new” TMVA features like the MethodDNN (root/tmva/tmva/inc/TMVA/MethodDNN.h). It’s also worth noting that I didn’t see the mention of some of these features in the ROOT release notes, either.
Is there a current document detailing all of the new features that have been added to TMVA over the past few years?
Much gratitude!
Brian C.
[1] tmva.sourceforge.net/docu/TMVAUsersGuide.pdf
[2] oproject.org/tiki-index.php?page=DeepLearning