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I've seen that there are four neural net packages in R:

  • neural
  • neuralnet
  • nnet
  • RSNNS
  • H2O

What are the advantages/disadvantages of those compared with each other?

As I found out NeuralNetTools only provides additional tools.

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    $\begingroup$ I would also add h2o's deeplearning to the list. It's one of the most powerful implementations of NNets accessible from R. And I think it scales up really well. $\endgroup$ – wacax Dec 23 '15 at 1:02
  • $\begingroup$ I primarily use h2o now, built in parallel processing and ram allocation is very nice. $\endgroup$ – TBSRounder Dec 23 '15 at 18:45
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take a look at these blogs- R for Deep Learning - 1 and R for Deep Learning - 2.

Hope it helps!

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    $\begingroup$ Not the most in-depth analysis of the packages themselves, but +1 for some information at least :-). I got the a little the impression the take away is "everything sucks", but maybe I am over-critical. $\endgroup$ – Make42 Oct 15 '16 at 14:40
  • $\begingroup$ Glad, it could help a lil, atleast. But no worries will try to find something more specific and will update you on that. Cheers! :). $\endgroup$ – Abhishek Jaiswal Oct 15 '16 at 14:44

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