This paper 3 proposes a new method to qualify the result given by a decision tree when it is used as a decision aid system. When the data are numerical, we compute the distance of ...
Abstract. In this paper, we investigate the properties of commonly used prepruning heuristics for rule learning by visualizing them in PN-space. PN-space is a variant of ROC-space,...
Abstract. We consider the problem of learning a mapping from question to answer messages. The training data for this problem consist of pairs of messages that have been received an...
This report contains derivations which did not fit into the paper [3]. Associative clustering (AC) is a method for separately clustering two data sets when one-to-one association...
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...