This is called supervised learning . This is called unsupervised learning . Our current research in pattern recognition is on classifier combination . The outputs of a set of classifiers are fused to get a more accurate or reliable classification decision. We are interested in the probabilistic background of classifier combination and the relationship between the dependence between the classifier outputs on the one hand, and the accuracy of the pool, on the other hand.
Fuzzy sets have a long history of admiration and condemnation.
When stripped off their inadequately ambitious claims to model human reasoning, fuzzy sets are quite a handy mathematical tool. We apply the basic theory to devise indices of contamination of Liverpool Bay and Morecambe Bay with heavy metals. Here is an example of our index of contamination of Morecambe Bay. HOME PAGE of the research group.