3 papers
cs.AI2025
Leveraging Association Rules for Better Predictions and Better Explanations
Gilles Audemard, Sylvie Coste-Marquis, Pierre Marquis +2
We present a new approach to classification that combines data and knowledge. In this approach, data mining is used to derive association rules (possibly with negations) from data.…
cs.LG2025
A Rectification-Based Approach for Distilling Boosted Trees into Decision Trees
Gilles Audemard, Sylvie Coste-Marquis, Pierre Marquis +2
We present a new approach for distilling boosted trees into decision trees, in the objective of generating an ML model offering an acceptable compromise in terms of predictive perf…
cs.AI2022
Rectifying Mono-Label Boolean Classifiers
Sylvie Coste-Marquis, Pierre Marquis
We elaborate on the notion of rectification of a Boolean classifier . Given and some background knowledge , postulates characterizing the way must be changed into a n…