Zobrazeno 1 - 10 of 21 pro vyhledávání: '"Ndeye Niang Keita"'
1
Sparse Correspondence Analysis
Autor: Gilbert Saporta, Ruiping Liu, Ndeye Niang Keita, Huiwen Wang
Publikováno v: ASMDA 2019. 18th Conference of the Applied Stochastic Models and Data Analysis International Society
ASMDA 2019. 18th Conference of the Applied Stochastic Models and Data Analysis International Society, Jun 2019, Florence, Italy
HAL
International audience; Since the introduction of the lasso in regression, various sparse methods have been developped in an unsupervised context like sparsePCA which is a combination of feature selection and dimension reduction. Their interest is to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::61c617ca165cd46c189567879eae3af1
https://hal-cnam.archives-ouvertes.fr/hal-02471317
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3
Le certificat « Analyste de données massives » du Conservatoire national des arts et métiers
Autor: Ndeye Niang Keita, Gilbert Saporta, Michel Crucianu, Philippe Rigaux
Publikováno v: Statistique et Enseignement
Statistique et Enseignement, Société Française de Statistique, 2016
HAL
We present the CNAM certificate dedicated to Big Data Analysis. The paper shortly presents the CNAM and its missions, the content of the training units, the public it is aimed for and how its specificities distinguish it from traditional courses in s
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3bf76eda7295faa3eb130c8e815385ca
https://hal-cnam.archives-ouvertes.fr/hal-02500566/file/CS59Stat_Ens.pdf
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4
Les méthodes « clusterwise » : principes et applications
Autor: Gilbert Saporta, Stéphanie Bougeard, Ndeye Niang-Keita
Publikováno v: XXII èmes rencontres de la Société Francophone de Classification
XXII èmes rencontres de la Société Francophone de Classification, Sep 2015, Nantes, France
HAL
International audience; Les méthodes « clusterwise » autrefois appelées « typologiques » consistent à optimiser simultanément une partition des unités statistiques et des modèles locaux. La régression clusterwise en est le cas le plus conn
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::671145980ec36a00e735ac3b1d502212
https://hal-cnam.archives-ouvertes.fr/hal-02507509
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5
Clusterwise multiblock PLS
Autor: Ndeye Niang-Keita, Stéphanie Bougeard, Gilbert Saporta, Hervé Abdi
Publikováno v: HAL
CARME 2015: Correspondence Analysis and Related Methods
CARME 2015: Correspondence Analysis and Related Methods, Sep 2015, Napoli, Italy
International audience
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a07e1fd9f5af8174a206011b8c5471cc
https://hal-cnam.archives-ouvertes.fr/hal-02507449
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6
Régression typologique pour données multi-blocs
Autor: Ndeye Niang Keita, Gilbert Saporta
Publikováno v: 46 ?mes journées de statistique
46 ?mes journées de statistique, Jun 2014, Rennes, France
HAL
46 émes journées de statistique
46 émes journées de statistique, Jun 2014, Rennes, France
International audience; Nous nous intéressons à la régression multi-blocs lorsque les individus présentent une structure en groupes inconnus a priori. la régression typologique (ou clusterwise) permet d?apporter une réponse dans le cas d'un seu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0bc251dd2a3ecaa4e8c417a5098a3a34
https://hal.archives-ouvertes.fr/hal-01126425
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7
Non parametric on-line control of batch processes based on STATIS and clustering
Autor: Ndeye Niang Keita, Flavio Fogliatto, Gilbert Saporta
Publikováno v: Journal de la Société Française de Statistique
Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2013, 154 (3), pp.124-142
HAL
Batch processes are widely used in several industrial sectors, e.g. food and pharmaceutical manufacturing.Process performance is described by variables which are monitored as the batch progresses. Data arising from such processes are usually monitore
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::bd543360175d204274f492e4976149b3
https://hal.archives-ouvertes.fr/hal-01126343/document
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8
Batch Process Monitoring by Three-way Data Analysis Approach
Autor: Ndeye Niang Keita, Flavio Fogliatto, Gilbert Saporta
Publikováno v: ASMDA'09 XIII International Conference on Applied Stochastic Models and Data Analysis
ASMDA'09 XIII International Conference on Applied Stochastic Models and Data Analysis, Jul 2009, Vilnius, Lithuania. pp.294-298
HAL
We propose a non parametric quality control strategy based on the three way method STATIS and convex hull peeling for monitoring batch processes with constant or variable duration. The method is illustrated on a simulated data set and on a real one.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4f1ef7edc6c780676da34a163eeb4072
https://hal.archives-ouvertes.fr/hal-01125669
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9
Resampling ROC curves
Autor: Ndeye Niang Keita, Gilbert Saporta
Publikováno v: Proceedings IASC 07
IASC'07 International Association for Statistical Computing
IASC'07 International Association for Statistical Computing, Aug 2007, Aveiro, Portugal
HAL
Resampling procedures allows a better use of ROC curves and AUC for predictive purposes. We also address a drawback of AUC for the comparison of ROC curves which are crossing, by recommending the use of partial AUC.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2779d74c5a5244ad7ce27c736baeeed4
https://hal.archives-ouvertes.fr/hal-01125359
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10
Correspondence Analysis and Classification
Autor: Gilbert Saporta, Ndeye Niang Keita
Publikováno v: Multiple Correspondence Analysis and Related Methods ISBN: 9781584886280
HAL
Multiple Correspondence Analysis and Related Methods
Michael Greenacre; Jörg Blasius. Multiple Correspondence Analysis and Related Methods, Chapman and Hall/CRC, pp.371-392, 2006, 9781584886280
J.Blasius M.Greenacre (editors) ,Chapman Hall
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52b237194045e5faec13856c9303b1b5
https://doi.org/10.1201/9781420011319.ch16
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