Contributions that would benefit this project

If you want to contribute code to Waffles, it must be:

We would prefer that it also:

but we might be willing to bend a little or help your code to meet these requirements if it is something of interest to us.

If you are looking to become a Waffles developer, and you want something to do, here are a few ideas for contributions that might be useful:

Add a new supervised learning algorithm. We are notably missing an SVM. Anyone know of a good QP solver in the public domain?
Our feature selection tools could benefit from more diversity of approaches.
Finding and reporting bugs is a very useful contribution.
Tell us where our tools are difficult to use. Seriously, sometimes we may not be as aware of usability issues as you think, and if you just tell us, we're often happy, even anxious, to fix them.
Contributions to our documentation are always welcome. (Documentation written by the original developers often makes too many assumptions about the reader already knowing nearly everything. Help us make our docs accessible to a more general audience.)
It would be really helpful if there was a document containing all of the bibtex info for the papers that one should cite when using any of these algorithms.
If you're a Debian or Red Hat package maintainer, we'd really love to have a package made with the Waffles command-line tools.
You could add your wishes to this list. (Of course, you cannot expect our developers to give your wishes priority over their own, but if you don't tell us what you want, you probably won't get it.)
I'd like GPU-based neural network implementations.
We need a good convolutional neural network with max pooling.
More testing and tune-up is needed with our multi-threaded ensemble methods.