Rang moyen et agrégation de classements
Recherche de partitions hiérarchisées optimales (-structure de hiérarchies optimales)
Reclassification, diversity and elementary number theory
Redescending M-estimators in regression analysis, cluster analysis and image analysis
We give a review on the properties and applications of M-estimators with redescending score function. For regression analysis, some of these redescending M-estimators can attain the maximum breakdown point which is possible in this setup. Moreover, some of them are the solutions of the problem of maximizing the efficiency under bounded influence function when the regression coefficient and the scale parameter are estimated simultaneously. Hence redescending M-estimators satisfy several outlier robustness...
Relations à «éloignement minimum» de relations binaires. Note bibliographique
Relative cost curves: An alternative to AUC and an extension to 3-class problems
Performance evaluation of classifiers is a crucial step for selecting the best classifier or the best set of parameters for a classifier. Receiver Operating Characteristic (ROC) curves and Area Under the ROC Curve (AUC) are widely used to analyse performance of a classifier. However, the approach does not take into account that misclassification for different classes might have more or less serious consequences. On the other hand, it is often difficult to specify exactly the consequences or costs...
Remark concerning a paradoxical situation in behaviour of error rate in discriminant analysis
Représentation ordonnée des classifications hiérarchiques
Représentations arborées des classifications