In the circle in the square problem the network must learn to classify points that are inside a circle and those that are not. In the sample files included with yawn the network must predict a "1" if the point is inside de circle and a "0" if not.
The figures bellow show the original test set and the predictions made by fuzzy ARTMAP and AppART. These figures were created with plot_cs.m, a matlab .m file included in the <yawndir>/data/circleinsquare directory. These results, in particular those of AppART are not optimal. For example, by increasing the <trainMatchVigilance> parameter a more precise but less generalizing approximation is obtained.
CinS test set

CinS test set contour

Fuzzy ARTMAP prediction of the test set

Contour of the fuzzy ARTMAP prediction of the test
set

AppART prediction of the test set  Contour of the AppART prediction of the test set 