A collection of machine learning and data mining algorithms and tools in C++. Developed by Mike Gashler and Eric Moyer Builds on 32 and 64-bit platforms, including Linux, Windows, OSX, etc. Distributed under the LGPL license.
Waffles provides the following command-line applications, each containing several tools for performing machine learning operations:
- waffles_cluster Tools for clustering.
- waffles_dimred Tools for dimensionality reduction, attribute selection, etc.
- waffles_generate Tools to sample distributions, sample manifolds, and generate certain types of data.
- waffles_learn Tools for supervised learning.
- waffles_plot Tools for visualizing data.
- waffles_recommend Tools for collaborative filtering, recommendation systems, imputation, etc.
- waffles_sparse Tools to learning from sparse data, document classification, etc.
- waffles_transform Tools for manipulating data, shuffling rows, swapping columns, matrix operations, etc.
- waffles_audio Tools for processing audio files.
- waffles_wizard For people who prefer not to have to remember commands, waffles also includes a graphical tool called
####waffles_wizard This application opens a web browser and guides the user through a series of forms to create a command that will perform the desired task. This provides all the convenience of a GUI interface, but without locking the user in. That is, since it generates a command-line command for you to use, it becomes easy to perform the same operations without the GUI. Thus, the Waffles tools are particularly well-suited for experiments that need to be automated. All of the functionality of the waffles tools is provided in an object-oriented C++ class library called
####GClasses The API, in other words, the command-line tools are just thin wrappers around functionality implemented in the GClasses library. Thus, if you find any of the operations performed by the Waffles command-line tools to be useful, it is easy to incorporate the same functionality into your C++ programs. Finally, in order to fully demonstrate how to use the GClasses library, several demo applications are also included with Waffles.