Stabilité d'un opérateur de classification
Stacked regression with restrictions
When we apply stacked regression to classification we need only discriminant indices which can be negative. In many situations, we want these indices to be positive, e.g., if we want to use them to count posterior probabilities, when we want to use stacked regression to combining classification. In such situation, we have to use leastsquares regression under the constraint βₖ ≥ 0, k = 1,2,...,K. In their earlier work [5], LeBlanc and Tibshirani used an algorithm given in [4]. However, in this paper...
Statistical approach to pattern recognition: Theory and practical solution by means of PREDITAS system
Statistical models for deformable templates in image and shape analysis
High dimensional data are more and more frequent in many application fields. It becomes particularly important to be able to extract meaningful features from these data sets. Deformable template model is a popular way to achieve this. This paper is a review on the statistical aspects of this model as well as its generalizations. We describe the different mathematical frameworks to handle different data types as well as the deformations. We recall the theoretical convergence properties of the estimators...
Statistische Modelle und Bayessche Verfahren zur Bestimmung einer unbekannten Klassifikation normalverteilter zufalliger Vektoren.
Structure géométrique des principaux indices de dissimilarité sur signes de présence-absence
Sur des approximations d'indices de dissimilarité via les représentations euclidienne et hiérarchique
Sur la proportion des paires de voisins réciproques pour une distribution uniforme dans un espace euclidien
Sur la séparabilité linéaire des enveloppes convexes des classes d'une CAH
Sur la valeur maxima des indices de niveau en classification ascendante hiérarchique dans le cas de l'agrégation par la distance moyenne
Sur l'analyse des données préalable à une classification automatique (proposition d'une nouvelle mesure de similarité)
Sur les orientations d'une ultramétrique ou d'une hiérarchie
Sur quelques aspects mathématiques des problèmes de classification automatique
Sur quelques aspects mathématiques des problèmes de classification automatique
Text document classification based on mixture models
Finite mixture modelling of class-conditional distributions is a standard method in a statistical pattern recognition. This paper, using bag-of-words vector document representation, explores the use of the mixture of multinomial distributions as a model for class-conditional distribution for multiclass text document classification task. Experimental comparison of the proposed model and the standard Bernoulli and multinomial models as well as the model based on mixture of multivariate Bernoulli distributions...
The likelihood ratio test for general mixture models with or without structural parameter
This paper deals with the likelihood ratio test (LRT) for testing hypotheses on the mixing measure in mixture models with or without structural parameter. The main result gives the asymptotic distribution of the LRT statistics under some conditions that are proved to be almost necessary. A detailed solution is given for two testing problems: the test of a single distribution against any mixture, with application to Gaussian, Poisson and binomial distributions; the test of the number of populations...
The likelihood ratio test for the number of components in a mixture with Markov regime
The likelihood ratio test for the number of components in a mixture with Markov regime
We study the LRT statistic for testing a single population i.i.d. model against a mixture of two populations with Markov regime. We prove that the LRT statistic converges to infinity in probability as the number of observations tends to infinity. This is a consequence of a convergence result of the LRT statistic for a subproblem where the parameters are restricted to a subset of the whole parameter set.
The possibilities of the linear discriminant method for decision
Theory of classification : a survey of some recent advances
The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.