Unsupervised learning using multivariate symbolic hybrid

One of the most challenging tasks in the area of knowledge discovery is to express learned knowledge in a form, which can be understood by domain experts (e.g. medical experts). In the paper we present our approach to unsupervised learning using multivariate symbolic hybrid. Main advantage of multimethod symbolic hybrid is that learned knowledge is expressed in a form of symbolic rules. Learned knowledge is much more understandable to domain experts, which increases its value and makes it much easier to apply.