Stéphane Lallich

发表

Improving Classification by Removing or Relabeling Mislabeled Instances

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2002, ISMIS.

Association Rule Interestingness Measures: Experimental and Theoretical Studies

Patrick Meyer, Philippe Lenca, Stéphane Lallich, 2007, Quality Measures in Data Mining.

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

Thierry Durand, Marie Hélène Metzger, Stéphane Lallich, 2012, BMC Medical Informatics and Decision Making.

Optimization of Self-Organizing Maps Ensemble in Prediction

Stéphane Lallich, Elie Prudhomme, 2008, DMIN.

Industrial Location Of Innovative Activities And Techno-Industrial Clusters: Astructuralist Approach To National Innovation Systems

Christian Le Bas, Stéphane Lallich, C. L. Bas, 2006 .

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

Olivier Teytaud, Stéphane Lallich, Elie Prudhomme, 2004, EGC.

Classification associative basée sur le Boosting

Stéphane Lallich, Emna Bahri, 2010, EGC.

Unsupervised feature construction for improving data representation and semantics

Stéphane Lallich, Julien Velcin, Marian-Andrei Rizoiu, 2013, Journal of Intelligent Information Systems.

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

Stéphane Lallich, Emna Bahri, 2009, EGC.

Association Rule Interestingness: Measure and Statistical Validation

Olivier Teytaud, Stéphane Lallich, Elie Prudhomme, 2007, Quality Measures in Data Mining.

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

Philippe Lenca, Stéphane Lallich, Benoît Vaillant, 2008, Statistical Implicative Analysis.

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

Jean-Michel Jolion, Fabrice Muhlenbach, Stéphane Lallich, 2003, Pattern Recognit..

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

Philippe Lenca, Stéphane Lallich, Yannick Le Bras, 2009, PAKDD.

Improving Prediction by Weighting Class Association Rules

Stéphane Lallich, Emna Bahri, S. Lallich, 2009, 2009 International Conference on Machine Learning and Applications.

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

Patrick Meyer, Philippe Lenca, Stéphane Lallich, 2008, Eur. J. Oper. Res..

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

Philippe Lenca, Stéphane Lallich, Benoît Vaillant, 2006, DMIN.

A Study of the Robustness of Association Rules

Philippe Lenca, Stéphane Lallich, Jérôme Azé, 2007, DMIN.

First Workshop Quality Issues, Measures of Interestingness and Evaluation of data mining models (PAKDD-QIMIE'09), Bangkok, Thailand

Philippe Lenca, Stéphane Lallich, 2009 .

Constrained independence for detecting interesting patterns

Philippe Lenca, Stéphane Lallich, Thomas Delacroix, 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Identifying and Handling Mislabelled Instances

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2004, Journal of Intelligent Information Systems.

Boosting Neighborhood-Based Classifiers

Richard Nock, Marc Sebban, Stéphane Lallich, 2001, ICML.

Separability Index in Supervised Learning

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2002, PKDD.

Semantic-enriched visual vocabulary construction in a weakly supervised context

Stéphane Lallich, Julien Velcin, Marian-Andrei Rizoiu, 2015, Intell. Data Anal..

Computing the Mutual Constrained Independence Model

Philippe Lenca, Stéphane Lallich, Thomas Delacroix, 2017 .

Amélioration d'une classification par filtrage des exemples mal étiquetés

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2002, EGC.

Une approche ensembliste inspirée du boosting en classification non supervisée

Romain Billot, Stéphane Lallich, Henri-Maxime Suchier, 2008, EGC.

MaxMin Linear Initialization for Fuzzy C-Means pdf

Jérôme Darmont, Stéphane Lallich, Aybüke Öztürk, 2018, MLDM.

A Visual Quality Index for Fuzzy C-Means pdf

Jérôme Darmont, Stéphane Lallich, Aybüke Öztürk, 2018, AIAI.

Mesurer l'intérêt des règles d'association

Patrick Meyer, Philippe Lenca, Stéphane Lallich, 2005, EGC.

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

Thanh-Nghi Do, Nguyen-Khang Pham, Philippe Lenca, 2009, EGC.

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

Richard Nock, Marc Sebban, Stéphane Lallich, 2003, J. Mach. Learn. Res..

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

Sorin Moga, Philippe Lenca, Stéphane Lallich, 2009, 2009 International Conference on Machine Learning and Applications.

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

Stéphane Lallich, Elie Prudhomme, Elie Prudhomme, 2007, European Grid Conference.

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

Stéphane Lallich, Ricco Rakotomalala, S. Di Palma, 1999, PKDD.

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

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2004, Discovery Science.

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

Stéphane Lallich, 1999, PKDD.

Validation statistique des cartes de Kohonen en apprentissage supervisé

Stéphane Lallich, Elie Prudhomme, 2005, EGC.

A Clustering of Interestingness Measures

Philippe Lenca, Stéphane Lallich, Benoît Vaillant, 2004, Discovery Science.

Structuring Typical Evolutions Using Temporal-Driven Constrained Clustering

Stéphane Lallich, Julien Velcin, Marian-Andrei Rizoiu, 2012, 2012 IEEE 24th International Conference on Tools with Artificial Intelligence.

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

Philippe Lenca, Stéphane Lallich, Yannick Le Bras, 2011, Discovery Science.

A Hybrid Approach of Boosting Against Noisy Data

Stéphane Lallich, Mondher Maddouri, Emna Bahri, 2009, Mining Complex Data.

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

Stéphane Lallich, Julien Velcin, Marian-Andrei Rizoiu, 2014, Int. J. Artif. Intell. Tools.

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

Fabrice Muhlenbach, Stéphane Lallich, Fabrice Muhlenbach, 2009, 2009 Ninth IEEE International Conference on Data Mining.

OPTIMONOTONE MEASURES FOR OPTIMAL RULE DISCOVERY

Philippe Lenca, Stéphane Lallich, Yannick Le Bras, 2012, Comput. Intell..

Fast Feature Selection Using Partial Correlation for Multi-vaslued Attributes

Stéphane Lallich, Ricco Rakotomalala, R. Rakotomalala, 2000, PKDD.

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

Stéphane Bonnevay, Stéphane Lallich, Julien Velcin, 2015, Data Mining and Knowledge Discovery.

Construction d'arbres de décision par optimisation

Stéphane Lallich, Ricco Rakotomalala, 2002, Rev. d'Intelligence Artif..

Pruning for Extracting Class Association Rules Without Candidate Generation

Stéphane Lallich, Emna Bahri, 2009, DMIN.

Special Issue on the ASMDA International Symposium on Applied Stochastic Models and Data Analysis

Stéphane Lallich, D. Pastor, 2007 .

Guest editor's introduction: special issue on quality issues, measures of interestingness and evaluation of data mining models - Journal of Intelligent Information Systems

Philippe Lenca, Stéphane Lallich, 2015 .

Traitement des exemples atypiques en apprentissage par la régression

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2003, EGC.

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

Thanh-Nghi Do, Philippe Lenca, Stéphane Lallich, 2015, Vietnam Journal of Computer Science.

FCP-Growth: Class Itemsets for Class Association Rules

Stéphane Lallich, Emna Bahri, S. Lallich, 2009, FLAIRS.

Mesure formelle de la robustesse des règles d'association

Patrick Meyer, Philippe Lenca, Stéphane Lallich, 2012, Mesurer et évaluer la Qualité des Données et des Connaissances.

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

Philippe Lenca, Stéphane Lallich, 2015, Journal of Intelligent Information Systems.

A Robustness Measure of Association Rules

Patrick Meyer, Philippe Lenca, Stéphane Lallich, 2010, ECML/PKDD.

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

Stéphane Lallich, Elie Prudhomme, S. Lallich, 2008, ISMIS.

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

Philippe Lenca, Stéphane Lallich, Yannick Le Bras, 2010, Data Mining.

Etude expérimentale de mesures de qualité de règles d'associations

Philippe Lenca, Stéphane Lallich, Benoît Vaillant, 2004, EGC.

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

Thanh-Nghi Do, Nguyen-Khang Pham, Philippe Lenca, 2008, PAKDD.

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

Thanh-Nghi Do, Nguyen-Khang Pham, Philippe Lenca, 2009, EGC.

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

Thanh-Nghi Do, Nguyen-Khang Pham, Philippe Lenca, 2008, DMIN.

Fouille dans la structure de documents XML

Omar Boussaïd, Fadila Bentayeb, Stéphane Lallich, 2004, EGC.

Discovering Research Communities by Clustering Bibliographical Data

Fabrice Muhlenbach, Stéphane Lallich, Fabrice Muhlenbach, 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

Warehousing Complex Archaeological Objects pdf

Jérôme Darmont, Stéphane Lallich, Aybüke Öztürk, 2015, CONTEXT.

A statistical approach to class separability

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2005 .

A statistical approach for separability of classes

Fabrice Muhlenbach, Stéphane Lallich, Djamel A. Zighed, 2005 .

A Probabilistic Framework Towards the Parameterization of Association Rule Interestingness Measures

Philippe Lenca, Stéphane Lallich, Benoît Vaillant, 2007 .

Statistical inference and data mining: false discoveries control

Olivier Teytaud, Stéphane Lallich, O. Teytaud, 2006 .

LOCATION OF INNOVATING ACTIVITIES, INDUSTRIAL STRUCTURE AND TECHNO-INDUSTRIAL CLUSTERS IN THE FRENCH ECONOMY, 1985-1990. EVIDENCE FROM US PATENTING

Stéphane Lallich, Sophie Bergeron, S. Lallich, 1998 .

Formal Framework for the Study of Algorithmic Properties of Objective Interestingness Measures

Philippe Lenca, Stéphane Lallich, Yannick Le Bras, 2012 .