Rule mining
Python module with functions for mining bases of implications and association rules in binary datasets (both 2- and n-dimensional). Also allows for the computation and handling of n-dimensional formal concepts.
Based on
- On Implication Bases in n-Lattices. Alexandre Bazin. Discrete Applied Mathematics 2020. (Abstract) (pdf)
- A Depth-first Search Algorithm for Computing Pseudo-closed Sets. Alexandre Bazin. Discrete Applied Mathematics 2018. (Abstract) (pdf)
- Représentation condensée de règles d’association multidimensionnelles. Alexandre Bazin, Aurélie Bertaux, Christophe Nicolle. EGC 2019. (Abstract : English, Français) (pdf)
- Reduction and Introducers in d-contexts. Alexandre Bazin and Giacomo Kahn. ICFCA 2019. (Abstract) (pdf)
- k-Partite Graphs as Contexts. Alexandre Bazin and Aurélie Bertaux. CLA 2018. (Abstract) (pdf)
Multicriteria decision making
Python module with functions for explaining the presence of alternatives on a Pareto front with background knowledge on the criteria.
Based on
- Explaining multicriteria decision making with formal concept analysis. Alexandre Bazin, Miguel Couceiro, Marie-Dominique Devignes and Amedeo Napoli. CLA 2020. (Abstract) (pdf)
Characterization of dataset features
Python module for selecting the most important features in a supervised classification dataset and interpreting them in terms of prediction and discrimination.
Based on
- An Approach to Identifying the Most Predictive and Discriminant Features in Supervised Classification Problems. Alexandre Bazin, Miguel Couceiro, Marie-Dominique Devignes, Amedeo Napoli. ICCS 2021, short paper. (Abstract) (pdf)
RNAseq clustering
Software for clustering RNA sequences. Click here for a comparison of its performance with other similar software.
Based on