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- overview

- data structures

- preprocessing

- networks

- classification

- graphing

- examples

 

NetMaker is a freeware package for building neural networks. It was developed primarily to support particle interaction classification in the high energy physics experiments at CERN - SMC, COMPASS, and the ICARUS, a neutrino experiment at LNGS. It was also my test-bed for experiments with various algorithms (some well known and some of my own ideas). Now it turned into a network designer with many possible applications - the idea is to have networks, pre- / post-processing and data sets split into uniformly working, task independent blocks which may form bigger systems. >>

neural engine features
papers

Download current version:  v0.9.5.2

Bayesian Framework features are available now, as a result of our latest work on EM form factor parametrizations.

- history of changes

previous versions:

v0.9.4.3
v0.9.3.4
v0.9.2.8
v0.9.2.0

ROOT interface with an example.
(ROOT homepage)

ROOT-based C++ code to run the trained network in your programs.

The page is translated to Serbo-Croatian language by Web Geeks.

Shall you have any questions, comments - e-mail me.

NetMaker window

• clear visualization of input data and network results:
      · specialized plots - purity-efficiency, background rejection,
      · histograms - with μ and σ of the distribution,
      · scatter plots - with Rxy linear correlation coefficient,
      · training parameters vs iteration,
      · real-time updated plots;
• written in C#;
• calculations optimized in C/asm (SSE2/SSE3/SSE4.1 aware).