In this paper, the notion of a fuzzy vector of normalized weights is introduced, and its application in decision making models based on the weighted average operation is studied. T...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
We derive the distribution of the number of links and the average weight for the shortest path tree (SPT) rooted at an arbitrary node to m uniformly chosen nodes in the complete g...
Remco van der Hofstad, Gerard Hooghiemstra, Piet V...
The paper presents a new method of decision tree induction based on formal concept analysis (FCA). The decision tree is derived using a concept lattice, i.e. a hierarchy of cluster...