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Neuroph for Linux 2.9 freeware
... classes which correspond to basic NN concepts. Also has nice GUI neural network editor to quickly create Java neural network components. It has been released as open source under the Apache 2.0 license, and it's FREE for you to use it. ...
| Author | Zoran Sevarac |
| Released | 2014-11-20 |
| Filesize | 210.00 MB |
| Downloads | 996 |
| OS | Linux |
| Installation | Instal And Uninstall |
| Keywords | neural network, neural network architectures, NN concept, neural, architecture |
| Users' rating (21 rating) |
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| Our rating |
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Neuroph for Linux Free Download - we do not host any Neuroph for Linux torrent files or links of Neuroph for Linux on rapidshare.com, depositfiles.com, megaupload.com etc. All Neuroph for Linux download links are direct Neuroph for Linux download from publisher site or their selected mirrors.
| 2.9 | Nov 20, 2014 | New Release | Update center for NeurophStudio is available at http://neuroph.sourceforge.net/neurophstudio-uc/updates.xml You can check and get updates online automaticaly! Maven repository: http://neuroph.sourceforge.net/maven2/ SVN: http://svn.code.sf.net/p/neuroph/code/trunk |
| 2.85 | Aug 24, 2014 | New Release | Update center for NeurophStudio is available at http://neuroph.sourceforge.net/neurophstudio-uc/updates.xml You can check and get updates online automaticaly! Maven repository: http://neuroph.sourceforge.net/maven2/ SVN: http://svn.code.sf.net/p/neuroph/code/trunk |
| 2.7 | Jan 11, 2013 | New Release | 1. Performance improvements about 30% thanks to use of plain arrays instead of ArrayList collection for storing layers, neurons and connections (thanks to Borislav Markov on idea and help with this) 2. Listing of supported input functions, transfer functions, learning rues, neuron and layer classes using API - through Neuroph class 3. New class DataSet which replace old TrainingSet class (beside nameing change which now prevents confusion with Test and Validation sets, there are some implementation changes and same class is used for storing supervised and unsupervised data sets) 4. Greatly improved visual editor in Neuroph Studio with full component pallete - everything you have on framework level now you can simpy drag n' drop (thanks to Marjan Hrzic and Uros Stojkic from University of Belgrade for help with this) 5. Weights histogram in Neuroph Studio (thanks to prof Maureen Doyle, Jim Neilan and Raj Akula from Northern Kentucky University for this contribution) |
