This package provides the Python "pyneurgen" module, which contains several classes for implementing grammatical evolution, a form of genetic programming, and classes for neural networks. These classes enable the creation of hybrid models that can embody the strengths.

While neural networks can be adept at solving non-linear problems, some problems remain beyond reach. For example, a difficult search space can cause suboptimal solutions to be reached. Also, multiobjective problems become extremely difficult, if not impossible. With genetic algorithms, a more thorough search can be made.

This latest version has additional features added to enable the construction of recurrent neural networks easier. Recurrent neural networks are used with time series data, because the structure of the network enables a memory of past events to be included in the process.

There is an additional helper class that configures such recurrent network types as Elman Simple Recurrent Network, Jordan style recurrent networks, and NARX (Non-Linear AutoRegressive with eXogenous inputs) recurrent networks. And, there are instructions on making your own structures for your unique requirements.

python setup.py install

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

See the LICENSE file included in this archive