This paper proposes a new evaluation strategy for productbased possibilistic networks learning algorithms. The proposed strategy is mainly based on sampling a possibilistic networks in order to construct an imprecise data set representative of their underlying joint distribution. Experimental results showing the efficiency of the proposed method in comparing existing possibilistic networks learning algorithms is also presented.
CITATION STYLE
Haddad, M., Leray, P., & Ben Amor, N. (2015). Evaluating product-based possibilistic networks learning algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9161, pp. 312–321). Springer Verlag. https://doi.org/10.1007/978-3-319-20807-7_28
Mendeley helps you to discover research relevant for your work.