I coded a tiny optimization framework in C++11 over the weekend. It contains a genetic algorithm and a neural network with classic backpropagation (project is on github).

Hello everyone,

As mentiond in the title, the project contains implementations for a neural network, a genetic algorithm, some statistics functions (mean, variance, covariance, pearson's R2) and a linear scaling method for shifting data.

I haven't paid much attention to design yet (lost a lot of time reading about rprop and levenberg-marquardt methods for ann training - hopefully they will be implemented soon), but the code is fairly simple so maybe it'll be useful to anyone looking for some code samples.

The repo is here: https://github.com/bburlacu/meta

Feedback or suggestions (even algorithm requests) would be appreciated. Thanks :)