In this paper, we study how to explain end-users the inference results of possibilistic rule-based systems. We formulate a necessary and sufficient condition for justifying by relevant subset rule premises possibility degree each output attribute value. apply functions reduce selected premises, in order form two kinds explanations: justification unexpectedness an The is composed expressions tha...

Feature construction can contribute to comprehensibility and performance of machine learning models. Unfortunately, it usually requires exhaustive search in the attribute space or time-consuming human involvement generate meaningful features. We propose a novel heuristic approach for reducing based on aggregation instance-based explanations predictive The proposed Explainable Construction (EFC)...

Natural selection explains how living forms are fitted to their conditions of life. Darwin argued that selection also explains what he called “the gradual advancement of the organisation,” i.e. evolutionary progress. Present-day selectionists disagree. In their view, it is happenstance that sustains conditions favorable to progress, and therefore happenstance, not selection, that explains progr...