×

L’algorithme SEM: Un algorithme d’apprentissage probabiliste pour la reconnaissance de mélange de densités. (The SEM algorithm: An algorithm of probabilistic learning for the determination of mixtures of densities). (French) Zbl 0607.62037


MSC:

62F99 Parametric inference
65C99 Probabilistic methods, stochastic differential equations
62H30 Classification and discrimination; cluster analysis (statistical aspects)
65D15 Algorithms for approximation of functions

References:

[1] Agrawala . - ” Learning with a probabilistic teacher ” IEEE. Information theory , Vol. 16 , nu. 4. Zbl 0207.49302 · Zbl 0207.49302 · doi:10.1109/TIT.1970.1054472
[2] BRYANT - WYLLIAMSON. - ” Asymptotic behaviour of classification maximum likelihood estimates ”. Biometrika 78 , Vol. 68 . Zbl 0393.62011 · Zbl 0393.62011 · doi:10.1093/biomet/65.2.273
[3] CELEUX, DIEBOLT. - Reconnaissance de mélange de densité et classification, un algorithme d’apprentissage probabiliste : l’algorithme SEM . Rapport de recherche INRIA n^\circ 349 . · Zbl 0607.62037
[4] Cooper . - ” Non supervised adaptative signal detection and pattern recognition ”. Information and Control , Vol. 7 . Zbl 0199.22402 · Zbl 0199.22402 · doi:10.1016/S0019-9958(64)90502-9
[5] DAY. - ” Estimating the components of a mixture of normal distributions ”. Biometrika 69, Vol. 56 . MR 254956 | Zbl 0183.48106 · Zbl 0183.48106 · doi:10.1093/biomet/56.3.463
[6] DIDAY et collaborateurs. - Optimisation en classification automatique . Editeur : INRIA . Zbl 0471.62056 · Zbl 0471.62056
[7] DEMPSTER - LAIRD - RUBIN. - ” Maximum likelihood from incomplete data via the EM algorithm ”. JRSS.B. , Vol. 39 . Zbl 0364.62022 · Zbl 0364.62022
[8] EVERITT - HAND. - Finite mixture distributions . Chapman and Hall . Zbl 0466.62018 · Zbl 0466.62018
[9] Marriott . - ” Separating mixtures of normal distributions ”. Biometrika , 31 . Zbl 0308.62050 · Zbl 0308.62050 · doi:10.2307/2529563
[10] MAKOV - SMITH. - ” Quasi Bayes procedures for unsupervised learning ”. Proc. IEEE. Conf. on Decision and Control. · Zbl 0397.62004
[11] Pearson . - ” Contribution to the mathematic theory of evolution ”. Philos. Trans. Soc. , nu. 185 ( 1894 ). · JFM 25.0347.02
[12] Quandt , Ramsey. - ” Estimating mixtures of normal distributions and switching regression ”. JASA , Vol. 73 . Zbl 0401.62024 · Zbl 0401.62024 · doi:10.2307/2286266
[13] REDNER - WALKER. - ” Mixture densities, maximum likelihood and the EM algorithm ”. SIAM Review , Vol. 26 , No. 2 , April 84. MR 738930 | Zbl 0536.62021 · Zbl 0536.62021 · doi:10.1137/1026034
[14] Schroeder . - ” Analyse d’un mélange de distribution de probabilité de même type ”. RSA , Vol. 24 , nu. 1. Numdam
[15] SCOTT - SYMONS. - ” Clustering methods based on likelihood ratio criteria ”. Biometrics , Vol. 27 .
[16] Shlezinger . - ” An algorithm for solving the selforganization problem ”. Cybernetics , nu. 2.
[17] Silverman . - ” Some asymptotic properties of the probabilistic teacher ” IEEE. Information theory , Vol. 26 , nu. 2. MR 570331 | Zbl 0428.62026 · Zbl 0428.62026 · doi:10.1109/TIT.1980.1056150
[18] SMITH - MAKOV. - ” A quasi Bayes sequential procedure for mixtures ”. JRSS. B. , Vol. 40 , nu. 1. MR 512148 | Zbl 0377.62045 · Zbl 0377.62045
[19] Teicher . - ” Identifiability of finite mixture ”. Ann. Math. Statist. , Vol. 34 . Article | MR 155376 · Zbl 0146.39302
[20] Symons . - ” Clustering criteria and multivariate normal mixtures ”. Biometrics , Vol. 37 . MR 673031 | Zbl 0473.62048 · Zbl 0473.62048 · doi:10.2307/2530520
[21] Wolfe . - ” Pattern clustering by multivariate mixture analysis ”. Multiv. Behav. Res. , Vol. 5 .
[22] YAKOWITZ - SPRAGINS. - ”On the identifiability of finite mixtures” . Ann. Math. Statist. , Vol. 39 . Article | MR 224204 | Zbl 0155.25703 · Zbl 0155.25703 · doi:10.1214/aoms/1177698520
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.