Stéphane Lallich

Inf. Sci., 2022

2018

MaxMin Linear Initialization for Fuzzy C-Means.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2018

A Visual Quality Index for Fuzzy C-Means.

[BibT_eX]

[DOI]

Aybüke Öztürk

Jérôme Darmont

Proceedings of the Artificial Intelligence Applications and Innovations, 2018

2016

ClusPath: a temporal-driven clustering to infer typical evolution paths.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2016

2015

Classifying many-class high-dimensional fingerprint datasets using random forest of oblique decision trees.

[BibT_eX]

[DOI]

Thanh-Nghi Do

Vietnam. J. Comput. Sci., 2015

Guest editor's introduction: special issue on quality issues, measures of interestingness and evaluation of data mining models.

[BibT_eX]

[DOI]

J. Intell. Inf. Syst., 2015

Comparison of two topological approaches for dealing with noisy labeling.

[BibT_eX]

[DOI]

Neurocomputing, 2015

Semantic-enriched visual vocabulary construction in a weakly supervised context.

[BibT_eX]

[DOI]

Intell. Data Anal., 2015

Constrained independence for detecting interesting patterns.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Warehousing Complex Archaeological Objects.

[BibT_eX]

[DOI]

Proceedings of the Modeling and Using Context, 2015

2014

How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, 2014

2013

Unsupervised feature construction for improving data representation and semantics.

[BibT_eX]

[DOI]

J. Intell. Inf. Syst., 2013

2012

Mesure formelle de la robustesse des règles d'association.

[BibT_eX]

[DOI]

Proceedings of the Mesurer et évaluer la Qualité des Données et des Connaissances, 2012

The use of regional platforms for managing electronic health records for the production of regional public health indicators in France.

[BibT_eX]

[DOI]

BMC Medical Informatics Decis. Mak., 2012

Optimonotone Measures for Optimal Rule Discovery.

[BibT_eX]

[DOI]

Comput. Intell., 2012

Structuring Typical Evolutions Using Temporal-Driven Constrained Clustering.

[BibT_eX]

[DOI]

Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

2011

Mining Classification Rules without Support: an Anti-monotone Property of Jaccard Measure.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 14th International Conference, 2011

2010

Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property.

[BibT_eX]

[DOI]

Proceedings of the Data Mining - Special Issue in Annals of Information Systems, 2010

Discovering Research Communities by Clustering Bibliographical Data.

[BibT_eX]

[DOI]

Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence, 2010

A Robustness Measure of Association Rules.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Classification associative basée sur le Boosting.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2010), 2010

2009

A Hybrid Approach of Boosting Against Noisy Data.

[BibT_eX]

[DOI]

Proceedings of the Mining Complex Data, 2009

On Optimal Rule Mining: A Framework and a Necessary and Sufficient Condition of Antimonotonicity.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009

All-Monotony: A Generalization of the All-Confidence Antimonotony.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2009

Improving Prediction by Weighting Class Association Rules.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2009

A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters.

[BibT_eX]

[DOI]

Proceedings of the ICDM 2009, 2009

FCP-Growth: Class Itemsets for Class Association Rules.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Second International Florida Artificial Intelligence Research Society Conference, 2009

Un nouvel algorithme de forêts aléatoires d'arbres obliques particulièrement adapté à la classification de données en grandes dimensions.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2009), 2009

FCP-Growth, une adaptation de FP-Growth pour générer des règles d'association de classe.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2009), 2009

Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Management [Best of EGC 2009, 2009

Pruning for Extracting Class Association Rules Without Candidate Generation.

[BibT_eX]

Proceedings of The 2009 International Conference on Data Mining, 2009

2008

On the behavior of the generalizations of the intensity of implication: A data-driven comparative study.

[BibT_eX]

[DOI]

Proceedings of the Statistical Implicative Analysis, Theory and Applications, 2008

On selecting interestingness measures for association rules: User oriented description and multiple criteria decision aid.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., 2008

A Comparison of Different Off-Centered Entropies to Deal with Class Imbalance for Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

Maps Ensemble for Semi-Supervised Learning of Large High Dimensional Datasets.

[BibT_eX]

[DOI]

Proceedings of the Foundations of Intelligent Systems, 17th International Symposium, 2008

Une approche ensembliste inspirée du boosting en classification non supervisée.

[BibT_eX]

[DOI]

Romain Billot

Henri-Maxime Suchier

Proceedings of the Extraction et gestion des connaissances (EGC'2008), 2008

Optimization of Self-Organizing Maps Ensemble in Prediction.

[BibT_eX]

Proceedings of The 2008 International Conference on Data Mining, 2008

Using Local Node Information in Decision Trees: Coupling a Local Labeling Rule with an Off-centered Entropy.

[BibT_eX]

Proceedings of The 2008 International Conference on Data Mining, 2008

Représentation des données par un comité de cartes auto-organisatrices : une application aux données bruitées.

[BibT_eX]

[DOI]

Proceedings of the Apprentissage Artificiel et Fouille de Données, 2008

2007

Association Rule Interestingness Measures: Experimental and Theoretical Studies.

[BibT_eX]

[DOI]

Proceedings of the Quality Measures in Data Mining, 2007

Association Rule Interestingness: Measure and Statistical Validation.

[BibT_eX]

[DOI]

Olivier Teytaud

Proceedings of the Quality Measures in Data Mining, 2007

Ensemble prédicteur fondé sur les cartes auto-organisatrices adapté aux données volumineuses.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2007), 2007

A Study of the Robustness of Association Rules.

[BibT_eX]

Proceedings of the 2007 International Conference on Data Mining, 2007

2006

Modeling of the counter-examples and association rules interestingness measures behavior.

[BibT_eX]

Proceedings of the 2006 International Conference on Data Mining, 2006

2005

Mesurer l'intérêt des règles d'association.

[BibT_eX]

[DOI]

Proceedings of the Extraction des connaissances : Etat et perspectives (Ateliers de la conférence EGC'2005), 2005

Validation statistique des cartes de Kohonen en apprentissage supervisé.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2005), 2005

2004

Identifying and Handling Mislabelled Instances.

[BibT_eX]

[DOI]

J. Intell. Inf. Syst., 2004

Etude expérimentale de mesures de qualité de règles d'associations.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2004), 2004

Contrôle du risque multiple pour la sélection de règles d'association significatives.

[BibT_eX]

[DOI]

Olivier Teytaud

Proceedings of the Extraction et gestion des connaissances (EGC'2004), 2004

Fouille dans la structure de documents XML.

[BibT_eX]

[DOI]

Proceedings of the Extraction et gestion des connaissances (EGC'2004), 2004

A Clustering of Interestingness Measures.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science, 7th International Conference, 2004

Outlier Handling in the Neighbourhood-Based Learning of a Continuous Class.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science, 7th International Conference, 2004

2003

A test to control a region growing process within a hierarchical graph.

[BibT_eX]

[DOI]

Jean-Michel Jolion

Pattern Recognit., 2003

Traitement des exemples atypiques en apprentissage par la régression.

[BibT_eX]

Proceedings of the Extraction et gestion des connaissances (EGC'2003), 2003

2002

Construction d'arbres de décision par optimisation.

[BibT_eX]

[DOI]

Ricco Rakotomalala

Rev. d'Intelligence Artif., 2002

Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem.

[BibT_eX]

[DOI]

Marc Sebban

Richard Nock

J. Mach. Learn. Res., 2002

Separability Index in Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

Improving Classification by Removing or Relabeling Mislabeled Instances.

[BibT_eX]

[DOI]

Proceedings of the Foundations of Intelligent Systems, 13th International Symposium, 2002

Amélioration d'une classification par filtrage des exemples mal étiquetés.

[BibT_eX]

Proceedings of the Extraction et gestion des connaissances (EGC'2002), 2002

2001

Boosting Neighborhood-Based Classifiers.

[BibT_eX]

Marc Sebban

Richard Nock

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000

Fast Feature Selection Using Partial Correlation for Multi-vaslued Attributes.

[BibT_eX]

[DOI]

Ricco Rakotomalala

Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

1999

Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept.

[BibT_eX]

[DOI]

Ricco Rakotomalala

S. Di Palma

Proceedings of the Principles of Data Mining and Knowledge Discovery, 1999

ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables.

[BibT_eX]

[DOI]