Abstract
We present a radial-basis adaptive resonance theory map and its application to classification problems. In order to classify input data, the system generates radial-basis categories. Two key parameters can control the number and size of the categories. Performing numerical experiments for two types of traditional expectant mothers, we have investigated the effects of key parameters on the classification functions.
