T. Abudawood and P. A. Flach, Evaluation measures for multi-class subgroup discovery, ECML PKDD, pp.35-50, 2009.

M. Atzmueller and F. Puppe, Sd-map-a fast algorithm for exhaustive subgroup discovery, pp.6-17, 2006.

M. Boley, C. Lucchese, D. Paurat, and T. Gärtner, Direct local pattern sampling by efficient two-step random procedures, pp.582-590, 2011.

M. Boley, S. Moens, and T. Gärtner, Linear space direct pattern sampling using coupling from the past, pp.69-77, 2012.

G. Bosc, J. Boulicaut, C. Ra¨?ssira¨?ssi, and M. Kaytoue, Anytime discovery of a diverse set of patterns with monte carlo tree search, DMKD, vol.32, issue.3, pp.604-650, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01418663

A. Buzmakov, S. O. Kuznetsov, and A. Napoli, Fast generation of best interval patterns for nonmonotonic constraints, ECML PKDD, pp.157-172, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01186718

A. Buzmakov, S. O. Kuznetsov, and A. Napoli, Revisiting pattern structure projections, Formal Concept Analysis, pp.200-215, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01186719

K. Denecke and S. L. Wismath, Galois connections and complete sublattices, Galois Connections and Applications, pp.211-229, 2004.

U. M. Fayyad and K. B. Irani, Multi-interval discretization of continuous-valued attributes for classification learning, pp.1022-1029, 1993.

B. Ganter and R. Wille, Formal Concept Analysis, 1999.

B. Ganter and S. O. Kuznetsov, Pattern structures and their projections, pp.129-142, 2120.

G. C. Garriga, P. Kralj, and N. Lavrac, Closed sets for labeled data, Journal of Machine Learning Research, vol.9, pp.559-580, 2008.

L. Geng and H. J. Hamilton, Interestingness measures for data mining: A survey, ACM Comput. Surv, vol.38, issue.3, 2006.

A. Giacometti and A. Soulet, Dense neighborhood pattern sampling in numerical data, SIAM. pp, pp.756-764, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01889220

H. Grosskreutz and S. Rüping, On subgroup discovery in numerical domains, Data Min. Knowl. Discov, vol.19, issue.2, pp.210-226, 2009.

T. Guyet, R. Quiniou, and V. Masson, Mining relevant interval rules, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01584981

Q. Hu and T. Imielinski, Alpine: Progressive itemset mining with definite guarantees, SIAM. pp, pp.63-71, 2017.

D. P. Huttenlocher, G. A. Klanderman, and W. Rucklidge, Comparing images using the hausdorff distance, IEEE Trans. Pat. Anal. Mach. Intell, vol.15, issue.9, pp.850-863, 1993.

M. Kaytoue, S. O. Kuznetsov, and A. Napoli, Revisiting Numerical Pattern Mining with Formal Concept Analysis, pp.1342-1347, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00600222

M. Kaytoue, S. O. Kuznetsov, A. Napoli, and S. Duplessis, Mining gene expression data with pattern structures in fca, Inf. Sci, vol.181, issue.10, 1989.

L. Kurgan and K. J. Cios, Discretization algorithm that uses class-attribute interdependence maximization, pp.980-987, 2001.

M. Van-leeuwen and A. J. Knobbe, Diverse subgroup set discovery, Data Min. Knowl. Discov, vol.25, issue.2, pp.208-242, 2012.

P. Lenca, P. Meyer, B. Vaillant, and S. Lallich, On selecting interestingness measures for association rules: User oriented description and multiple criteria decision aid, European Journal of Operational Research, vol.184, issue.2, pp.610-626, 2008.

T. Lucas, T. C. Silva, R. Vimieiro, and T. B. Ludermir, A new evolutionary algorithm for mining top-k discriminative patterns in high dimensional data, Appl. Soft Comput, vol.59, pp.487-499, 2017.

M. Mampaey, S. Nijssen, A. Feelders, and A. J. Knobbe, Efficient algorithms for finding richer subgroup descriptions in numeric and nominal data, ICDM. pp, pp.499-508, 2012.
DOI : 10.1109/icdm.2012.117

S. Morishita and J. Sese, Traversing itemset lattice with statistical metric pruning, ACM SIGMOD-SIGACT-SIGART, pp.226-236, 2000.
DOI : 10.1145/335168.335226

Z. Pawlak, Rough sets, International Journal of Parallel Programming, vol.11, issue.5, pp.341-356, 1982.

S. Roman, Lattices and Ordered Sets, 2008.

S. Wrobel, An algorithm for multi-relational discovery of subgroups, PKDD. pp, pp.78-87, 1997.
DOI : 10.1007/3-540-63223-9_108

Y. Yang, G. I. Webb, and X. Wu, Discretization methods, Data Mining and Knowledge Discovery Handbook, pp.101-116, 2010.

S. Zilberstein, Using anytime algorithms in intelligent systems, AI Magazine, vol.17, issue.3, pp.73-83, 1996.