Neuroph for Windows 2.9 freeware

Neuroph is lightweight Java neural network framework to develop common neural network architectures. It contains well designed, open source Java library with small number of basic 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 211.00 MB
Downloads 1017
OS Windows XP, Windows Vista, Windows 7
Installation Instal And Uninstall
Keywords neural network, neural network architectures, NN concept, neural, architecture
Users' rating
(11 rating)
Our rating 5 freeware award
Neuroph for Windows - Freeware Download Notice

Neuroph for Windows Free Download - we do not host any Neuroph for Windows torrent files or links of Neuroph for Windows on rapidshare.com, depositfiles.com, megaupload.com etc. All Neuroph for Windows download links are direct Neuroph for Windows download from publisher site or their selected mirrors.

Neuroph for Windows freeware - The Latest User Reviews
Neuroph for Windows freeware - The Latest Versions History
2.9 Nov 20, 2014 New Release
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)

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