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Project Info

11.09.2013.
Neuroph 2.8 Released

The version 2.8 of framework and GUI tool NeurophStudio has been released!

This release brings some great improvements in GUI NeurophStudio, handy new features on framework level and small API changes. Main changes include:

  1. Class DataSet moved from org.neuroph.core.learning to new package org.neuroph.core.data
  2. Added basic but extensible data set sampling
  3. Added BufferedDataset class which allowes buffered loading of data set. This is usefull for large datasets, and allows partial loading of data set during the training. It can be used as regular dataset. Just note that normalization and sampling methods wont work on entire dataset, just on the data currently loaded in memory.
  4. Normalization methods are now normalizing outputs too
  5. Added new event NeuralNetworkCalculated which is fired every time when neural network event is calculated.
  6. New interface ErrorFunction which allows custom error functions for learning rules to be defined. MeanSquaredError is provided as commonly used, default.
  7. New interface StopCondition which allows custom stop criteria for stopping learning rule execution to be defined. Some coommonly used are provided
  8. A bunch os source code samples for some problems from UCI machine learning repository at org.neuroph.samples (Samples module)
In NeurophStudio:
  1. Full featured visual editor - drag n drop components from pallete to build custom neural network, or use it to modify existing network created using wizard explore and change settings for each component
  2. 2D and 3D visualization of neural networks and data sets, see how data sets looks like and what is network doing
  3. Neuroph Studio Update Center - get the new features runing auto update!
  4. Brain Computer Interface (BCI) wizard - wizard to create neural network based barin wave recognizer/classifier
  5. BCI Tool - brain wave visualizer and EEG recorder using NeuroSky BCI
  6. Classifier evaluation tool based on GoodOldAi Framework (test classifier based on neural network from Neuroph and compare it with others)

DOWNLOADS

Downloads for this release are available at our downloads page

 

 

 

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