|ARTMAP Neural Networks:
API Docs for ARTMAP
- Inspired by biological neural networks, ARTMAP systems learn to associate arbitrary sequences of input/output pattern pairs
- With fast learning, ARTMAP can encode an input in a single presentation. Many alternative methods require thousands of training epochs.
- Fast learning lets ARTMAP networks do incremental learning, allowing an agent to interact with its environment in real time.
The documentation for the programmer's interface for the ARTMAP module is available here.
Source code for ARTMAP
The source code for the ARTMAP module is available in Zipped format here.
For a Java port of this code, see here.
If you just want to use the implementation, and don't need the source, you can use the ARTMAP implementation as a Dynamically Loadable Library (DLL).
A zip file containing the ARTMAP DLL is available here. It also contains the file ArtmapDll.lib, which is required for linking to the DLL. Also included is a simple example showing how to call the DLL: ArtmapDllTester.cpp, and a Visual C++ project file showing how to link to the DLL.
Versions of ARTMAP Provided
The module provided with the Classer toolkit implements four versions of the ARTMAP neural network:
The version that is used can be specified as a parameter via the setNetworkType() method call.
- Fuzzy ARTMAP
- Learns associations, and makes single-label predictions for arbitrary input samples
- See Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. Carpenter, G.A., Grossberg, S., Markuzon, N., Reynolds, J.H., & Rosen, D.B. (1992). IEEE Transactions on Neural Networks, 3, 698-713.
- Default ARTMAP
- Instance-Counting ARTMAP
- Distributed ARTMAP