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Stéphane Lallich
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- affiliation: Lumière University Lyon 2, France
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2020 – today
- 2022
- [j15]Thomas Delacroix, Philippe Lenca, Stéphane Lallich:
What to expect from a set of itemsets? Inf. Sci. 593: 314-340 (2022)
2010 – 2019
- 2018
- [c42]Aybüke Öztürk
, Stéphane Lallich, Jérôme Darmont
A Visual Quality Index for Fuzzy C-Means. AIAI 2018: 546-555 - [c41]Aybüke Öztürk
MaxMin Linear Initialization for Fuzzy C-Means. MLDM (1) 2018: 1-15 - [i7]Aybüke Öztürk, Stéphane Lallich, Jérôme Darmont
A Visual Quality Index for Fuzzy C-Means. CoRR abs/1806.01552 (2018) - [i6]Aybüke Öztürk, Stéphane Lallich, Jérôme Darmont
MaxMin Linear Initialization for Fuzzy C-Means. CoRR abs/1808.00197 (2018) - 2016
- [j14]Marian-Andrei Rizoiu
ClusPath: a temporal-driven clustering to infer typical evolution paths. Data Min. Knowl. Discov. 30(5): 1324-1349 (2016) - [i5]Marian-Andrei Rizoiu
How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions. CoRR abs/1601.02603 (2016) - [i4]Aybüke Öztürk, Louis Eyango, Sylvie Yona Waksman
Warehousing Complex Archaeological Objects. CoRR abs/1608.06469 (2016) - 2015
- [j13]Marian-Andrei Rizoiu
Semantic-enriched visual vocabulary construction in a weakly supervised context. Intell. Data Anal. 19(1): 161-185 (2015) - [j12]Fabien Rico, Fabrice Muhlenbach, Djamel A. Zighed, Stéphane Lallich:
Comparison of two topological approaches for dealing with noisy labeling. Neurocomputing 160: 3-17 (2015) - [j11]Philippe Lenca, Stéphane Lallich:
Guest editor's introduction: special issue on quality issues, measures of interestingness and evaluation of data mining models. J. Intell. Inf. Syst. 45(3): 295-297 (2015) - [j10]Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich:
Classifying many-class high-dimensional fingerprint datasets using random forest of oblique decision trees. Vietnam. J. Comput. Sci. 2(1): 3-12 (2015) - [c40]Aybüke Öztürk
Warehousing Complex Archaeological Objects. CONTEXT 2015: 226-239 - [c39]Thomas Delacroix, Ahcene Boubekki
Constrained independence for detecting interesting patterns. DSAA 2015: 1-10 - [i3]Marian-Andrei Rizoiu
ClusPath: A Temporal-driven Clustering to Infer Typical Evolution Paths. CoRR abs/1512.03501 (2015) - [i2]Marian-Andrei Rizoiu
Semantic-enriched Visual Vocabulary Construction in a Weakly Supervised Context. CoRR abs/1512.04605 (2015) - [i1]Marian-Andrei Rizoiu
Unsupervised Feature Construction for Improving Data Representation and Semantics. CoRR abs/1512.05467 (2015) - 2014
- [j9]Marian-Andrei Rizoiu
How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions. Int. J. Artif. Intell. Tools 23(4) (2014) - 2013
- [j8]Marian-Andrei Rizoiu
Unsupervised feature construction for improving data representation and semantics. J. Intell. Inf. Syst. 40(3): 501-527 (2013) - 2012
- [j7]Yannick Le Bras, Philippe Lenca, Stéphane Lallich:
Optimonotone Measures for Optimal Rule Discovery. Comput. Intell. 28(4): 475-504 (2012) - [j6]Marie Hélène Metzger
The use of regional platforms for managing electronic health records for the production of regional public health indicators in France. BMC Medical Informatics Decis. Mak. 12: 28 (2012) - [c38]Marian-Andrei Rizoiu
Structuring Typical Evolutions Using Temporal-Driven Constrained Clustering. ICTAI 2012: 610-617 - [p6]Yannick Le Bras, Patrick Meyer, Philippe Lenca, Stéphane Lallich:
Mesure formelle de la robustesse des règles d'association. Mesurer et évaluer la Qualité des Données et des Connaissances 2012: 71-88 - 2011
- [c37]Yannick Le Bras, Philippe Lenca, Stéphane Lallich:
Mining Classification Rules without Support: an Anti-monotone Property of Jaccard Measure. Discovery Science 2011: 179-193 - 2010
- [c36]Emna Bahri, Stéphane Lallich:
Classification associative basée sur le Boosting. EGC 2010: 501-512 - [c35]Yannick Le Bras, Patrick Meyer, Philippe Lenca, Stéphane Lallich:
A Robustness Measure of Association Rules. ECML/PKDD (2) 2010: 227-242 - [c34]Fabrice Muhlenbach, Stéphane Lallich:
Discovering Research Communities by Clustering Bibliographical Data. Web Intelligence 2010: 500-507 - [p5]Yannick Le Bras, Philippe Lenca, Stéphane Lallich:
Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property. Data Mining 2010: 75-98
2000 – 2009
- 2009
- [c33]Emna Bahri, Stéphane Lallich:
Pruning for Extracting Class Association Rules Without Candidate Generation. DMIN 2009: 11-17 - [c32]Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich, Nguyen-Khang Pham:
Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees. EGC (best of volume) 2009: 39-55 - [c31]Thanh-Nghi Do, Stéphane Lallich, Nguyen-Khang Pham, Philippe Lenca:
Un nouvel algorithme de forêts aléatoires d'arbres obliques particulièrement adapté à la classification de données en grandes dimensions. EGC 2009: 79-90 - [c30]Emna Bahri, Stéphane Lallich:
FCP-Growth, une adaptation de FP-Growth pour générer des règles d'association de classe. EGC 2009: 461-462 - [c29]Emna Bahri, Stéphane Lallich:
FCP-Growth: Class Itemsets for Class Association Rules. FLAIRS 2009 - [c28]Fabrice Muhlenbach, Stéphane Lallich:
A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters. ICDM 2009: 884-889 - [c27]Yannick Le Bras, Philippe Lenca, Sorin Moga, Stéphane Lallich:
All-Monotony: A Generalization of the All-Confidence Antimonotony. ICMLA 2009: 759-764 - [c26]Emna Bahri, Stéphane Lallich:
Improving Prediction by Weighting Class Association Rules. ICMLA 2009: 765-770 - [c25]Yannick Le Bras, Philippe Lenca, Stéphane Lallich:
On Optimal Rule Mining: A Framework and a Necessary and Sufficient Condition of Antimonotonicity. PAKDD 2009: 705-712 - [p4]Emna Bahri, Stéphane Lallich, Nicolas Nicoloyannis, Mondher Maddouri:
A Hybrid Approach of Boosting Against Noisy Data. Mining Complex Data 2009: 41-54 - 2008
- [j5]Philippe Lenca, Patrick Meyer, Benoît Vaillant, Stéphane Lallich:
On selecting interestingness measures for association rules: User oriented description and multiple criteria decision aid. Eur. J. Oper. Res. 184(2): 610-626 (2008) - [c24]Elie Prudhomme, Stéphane Lallich:
Représentation des données par un comité de cartes auto-organisatrices : une application aux données bruitées. AAFD 2008: 177-202 - [c23]Nguyen-Khang Pham, Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich:
Using Local Node Information in Decision Trees: Coupling a Local Labeling Rule with an Off-centered Entropy. DMIN 2008: 117-123 - [c22]Elie Prudhomme, Stéphane Lallich:
Optimization of Self-Organizing Maps Ensemble in Prediction. DMIN 2008: 683-688 - [c21]Romain Billot, Henri-Maxime Suchier, Stéphane Lallich:
Une approche ensembliste inspirée du boosting en classification non supervisée. EGC 2008: 361-372 - [c20]Elie Prudhomme, Stéphane Lallich:
Maps Ensemble for Semi-Supervised Learning of Large High Dimensional Datasets. ISMIS 2008: 100-110 - [c19]Philippe Lenca, Stéphane Lallich, Thanh-Nghi Do, Nguyen-Khang Pham:
A Comparison of Different Off-Centered Entropies to Deal with Class Imbalance for Decision Trees. PAKDD 2008: 634-643 - [p3]Benoît Vaillant, Stéphane Lallich, Philippe Lenca:
On the behavior of the generalizations of the intensity of implication: A data-driven comparative study. Statistical Implicative Analysis 2008: 421-447 - 2007
- [c18]Jérôme Azé, Philippe Lenca, Stéphane Lallich, Benoît Vaillant:
A Study of the Robustness of Association Rules. DMIN 2007: 163-169 - [c17]Elie Prudhomme, Stéphane Lallich:
Ensemble prédicteur fondé sur les cartes auto-organisatrices adapté aux données volumineuses. EGC 2007: 473-484 - [p2]Philippe Lenca, Benoît Vaillant, Patrick Meyer, Stéphane Lallich:
Association Rule Interestingness Measures: Experimental and Theoretical Studies. Quality Measures in Data Mining 2007: 51-76 - [p1]Stéphane Lallich, Olivier Teytaud, Elie Prudhomme:
Association Rule Interestingness: Measure and Statistical Validation. Quality Measures in Data Mining 2007: 251-275 - 2006
- [c16]Benoît Vaillant, Stéphane Lallich, Philippe Lenca:
Modeling of the counter-examples and association rules interestingness measures behavior. DMIN 2006: 132-137 - 2005
- [c15]Elie Prudhomme, Stéphane Lallich:
Validation statistique des cartes de Kohonen en apprentissage supervisé. EGC 2005: 79-90 - [c14]Benoît Vaillant, Patrick Meyer, Elie Prudhomme, Stéphane Lallich, Philippe Lenca, Sébastien Bigaret:
Mesurer l'intérêt des règles d'association. EGC (Ateliers) 2005: 421-426 - 2004
- [j4]Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed:
Identifying and Handling Mislabelled Instances. J. Intell. Inf. Syst. 22(1): 89-109 (2004) - [c13]Benoît Vaillant, Philippe Lenca, Stéphane Lallich:
A Clustering of Interestingness Measures. Discovery Science 2004: 290-297 - [c12]Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed:
Outlier Handling in the Neighbourhood-Based Learning of a Continuous Class. Discovery Science 2004: 314-321 - [c11]Stéphane Lallich, Elie Prudhomme, Olivier Teytaud:
Contrôle du risque multiple pour la sélection de règles d'association significatives. EGC 2004: 305-316 - [c10]Benoît Vaillant, Philippe Lenca, Stéphane Lallich:
Etude expérimentale de mesures de qualité de règles d'associations. EGC 2004: 341-352 - [c9]Amandine Duffoux, Omar Boussaid, Stéphane Lallich, Fadila Bentayeb:
Fouille dans la structure de documents XML. EGC 2004: 519-524 - 2003
- [j3]Stéphane Lallich, Fabrice Muhlenbach, Jean-Michel Jolion:
A test to control a region growing process within a hierarchical graph. Pattern Recognit. 36(10): 2201-2211 (2003) - [c8]Stéphane Lallich, Fabrice Muhlenbach, Djamel A. Zighed:
Traitement des exemples atypiques en apprentissage par la régression. EGC 2003: 399-410 - 2002
- [j2]Marc Sebban, Richard Nock, Stéphane Lallich:
Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. J. Mach. Learn. Res. 3: 863-885 (2002) - [j1]Ricco Rakotomalala, Stéphane Lallich:
Construction d'arbres de décision par optimisation. Rev. d'Intelligence Artif. 16(6): 685-703 (2002) - [c7]Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed:
Amélioration d'une classification par filtrage des exemples mal étiquetés. EGC 2002: 155-166 - [c6]Stéphane Lallich, Fabrice Muhlenbach, Djamel A. Zighed:
Improving Classification by Removing or Relabeling Mislabeled Instances. ISMIS 2002: 5-15 - [c5]Djamel A. Zighed, Stéphane Lallich, Fabrice Muhlenbach:
Separability Index in Supervised Learning. PKDD 2002: 475-487 - 2001
- [c4]Marc Sebban, Richard Nock, Stéphane Lallich:
Boosting Neighborhood-Based Classifiers. ICML 2001: 505-512 - 2000
- [c3]Stéphane Lallich, Ricco Rakotomalala:
Fast Feature Selection Using Partial Correlation for Multi-vaslued Attributes. PKDD 2000: 221-231
1990 – 1999
- 1999
- [c2]Stéphane Lallich:
ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables. PKDD 1999: 398-405 - [c1]Ricco Rakotomalala, Stéphane Lallich, S. Di Palma:
Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept. PKDD 1999: 510-517
Coauthor Index
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