Hierarchical classification inference for fuzzy data analysis

One of the main problems in fuzzy data analysis is the clustering of data. In this paper an expert system approach is followed. On the basis of training data sets a hierarchical knowledge tree is generated consisting of rules that are characterized by an increasing specificity. The hierarchical knowledge is used for inferring decisions on new data sets to be assessed. In order to reduce further the computational complexity the core zone index is introduced, which guarantees the optimal search level in the hierarchical knowledge tree.