Fuzzy Labeled Neural GAS for Fuzzy Classification
T. Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger · PUB – Publications at Bielefeld University (Bielefeld University) · 2005
We extend neural gas for supervised fuzzy classification. In this way we are able to learn crisp as well as fuzzy clustering, given labeled data. Based on the neural gas cost function, we propose three different ways to incorporate the additional class information into the learning algorithm. We demonstrate the effect on the location of the prototypes and the classification accuracy. Further, we show that relevance learning can be easily included.