Results 101 to 110 of about 3,867 (213)

Biclustering of ARMA time series

, 2010
Biclustering is a method of grouping objects and attributes simultaneously in order to find multiple hidden patterns. When dealing with a long time series, there is a low possibility of finding meaningful clusters of whole time sequence.
Lee, J, Jun, CH, Chi-Hyuck Jun, Jeonghwa Lee   +3 more
core   +1 more source

Assessing Sustainable Development Performance and Alternative Concepts in a Group of Developed Countries in Europe

Problemy Ekorozwoju
This study evaluates the progress of 31 countries, including EU member states, Norway, Iceland, Switzerland, and the United Kingdom (UK), towards the United Nations (UN) 2030 Agenda for Sustainable Development (SD) and its 17 Sustainable Development ...
Magdaléna Drastichová, Peter Filzmoser
doaj   +1 more source

Feature Grouping Technique Based on Biclustering for the Analysis of LC-MS Metabolomic Data

, 2011
Feature Grouping Technique Based on Biclustering for the Analysis of LC-MS Metabolomic ...
周丽娜, 许国旺, 林晓惠, 尹沛源, 阮强   +4 more
core  

Identifying Poverty Vulnerability Patterns in Indonesia using Cheng and Chruch’s Algorithm

JTAM (Jurnal Teori dan Aplikasi Matematika)
Poverty remains a significant issue in developing countries, including Indonesia, where in 2022, the number of people living in poverty reached 26.36 million, with a poverty rate of 9.57%.
Irsyifa Mayzela Afnan, Hari Wijayanto, Aji Hamim Wigena   +2 more
doaj   +1 more source

Efficient biclustering and its applications amid privacy constraints.

, 2007
Efficient biclustering and its applications amid privacy ...
Waseem. Ahmad (7958780)
core   +3 more sources

The Evolution of Biclustering Algorithms

Biclustering methods have been initially developed for solving tasks of finding local correlations between expressions of gene subsets in the subsets of conditions.
Kuļešova, Gaļina, Uzhga-Rebrov, Oleg
core  

Biclustering algorithms: A survey

, 2004
Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns.
Amos Tanay, Roded Sharan, Ron Shamir
core  

Biclustering Basé sur le Transport Optimal

, 2023
International audienceLes graphes bipartis peuvent être utilisés pour modéliser une grande variété d’informations dyadiques telles que les paires utilisateur-score, document-terme et gène-conditions expérimentales.
Labiod, Lazhar, Fettal, Chakib, Nadif, Mohamed   +2 more
core  

Bayesian biclustering in the presence of covariates: theory and applications

openIl biclustering rappresenta un'estensione del clustering tradizionale che permette di identificare simultaneamente gruppi di righe e colonne in matrici di dati ad alta dimensionalità.
VEGHIN, IRENE
core  

Biconvex Biclustering

This article proposes a biconvex modification to convex biclustering in order to improve its performance in high-dimensional settings. In contrast to heuristics that discard a subset of noisy features a priori, our method jointly learns and accordingly weighs informative features while discovering biclusters.
Rosen, Sam, Chi, Eric C., Xu, Jason
openaire   +2 more sources