Advertisement
Published in:
2015 | OriginalPaper | Chapter
A New View of Conformity and Its Application to Classification
Authors : Myriam Bounhas, Henri Prade, Gilles Richard
Published in: Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
The paper discusses a new way of estimating the conformity of an item, described in terms of Boolean-valued features, with respect to a class of items. A usual view of conformity is to compare, feature by feature, the item value with the corresponding distribution of values observed over the class. Then combining the comparison results for the different features yields a global conformity measure. In this paper, the item is rather compared to triples of elements taken in the class: it is checked if the item conforms, over a maximal number of features, to the majority of the elements in each triple. Based on the idea that a new item should be allocated the class to which it conforms the most, a simple classification algorithm is proposed. Experiments on a set of benchmarks show that it is competitive with classical methods.