Zobrazeno 1 - 4
of 4
pro vyhledávání: '"David Sergio Matusevich"'
Publikováno v:
Machine Learning. 102:483-504
Variable selection in high dimensional data is a challenging problem due to the exponential number of variable combinations, and Markov Chain Monte Carlo (MCMC) methods represent the state of the art to solve it. With genomics data this problem becom
Publikováno v:
Data and Knowledge Engineering
Data and Knowledge Engineering, Elsevier, 2013, 89, pp.38-54. ⟨10.1016/j.datak.2013.11.002⟩
Data and Knowledge Engineering, 2013, 89, pp.38-54. ⟨10.1016/j.datak.2013.11.002⟩
Data and Knowledge Engineering, Elsevier, 2013, 89, pp.38-54. ⟨10.1016/j.datak.2013.11.002⟩
Data and Knowledge Engineering, 2013, 89, pp.38-54. ⟨10.1016/j.datak.2013.11.002⟩
Mis en ligne le 19/12/2013; International audience; In a data mining project developed on a relational database, a significant effort is required to build a data set for analysis. The main reason is that, in general, the database has a collection of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38072fb816be81636dd60f7d0a1cbaa8
https://hal.archives-ouvertes.fr/hal-00940778
https://hal.archives-ouvertes.fr/hal-00940778
Publikováno v:
DTMBIO
Variable selection is a fundamental problem in Bayesian statistics whose solution requires exploring a combinatorial search space. We study the solution of variable selection with a well-known MCMC method, which requires thousands of iterations. We p
Publikováno v:
CIKM
Clustering is a fundamental problem in statistics and machine learning, whose solution is commonly computed by the Expectation-Maximization (EM) method, which finds a locally optimal solution for an objective function called log-likelihood. Since the