Results 21 to 30 of about 3,771,811 (275)
A-DVM: A Self-Adaptive Variable Matrix Decision Variable Selection Scheme for Multimodal Problems
Entropy, 2020 Artificial Bee Colony (ABC) is a Swarm Intelligence optimization algorithm well known for its versatility. The selection of decision variables to update is purely stochastic, incurring several issues to the local search capability of the ABC.
Marco Antonio Florenzano Mollinetti +3 more
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Application of variable selection and dimension reduction on predictors of MSE’s development
Journal of Big Data, 2019 Nature create variables using its character component, and variables are sharing characters from a vary small to relatively large scale. This results, variables to have from a vary different to a more similar character, and leads to have a relation ship.
Habtamu Tilaye Wubetie
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Variable selection in multivariate multiple regression.
PLoS ONE, 2020 IntroductionIn many practical situations, we are interested in the effect of covariates on correlated multiple responses. In this paper, we focus on estimation and variable selection in multi-response multiple regression models.
Asokan Mulayath Variyath, Anita Brobbey
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Identifying Plant Pentatricopeptide Repeat Proteins Using a Variable Selection Method
Frontiers in Plant Science, 2021 Motivation: Pentatricopeptide repeat (PPR), which is a triangular pentapeptide repeat domain, plays an important role in plant growth. Features extracted from sequences are applicable to PPR protein identification using certain classification methods ...
Xudong Zhao +5 more
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Group Variable Selection Methods with Quantile Regression: A Simulation Study. [PDF]
المجلة العراقية للعلوم الاحصائيةIn many cases, covariates have a grouping structure that can be used in the analysis to identify important groups and the significant members of those groups. This paper reviews some group variable selection methods that utilize quantile regression.
Hussein Hashem
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Fault Relevant Variable Selection for Fault Diagnosis
IEEE Access, 2020 In process monitoring, fault relevant variable selection and fault diagnosis are two important branches. But they are often discussed independently and scarcely integrated in research.
Ruixiang Deng +2 more
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Environmental Health, 2017 Background There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures ...
Jose Barrera-Gómez +14 more
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IEEE Access, 2022 Population health is multidimensional in nature, having complex relationships with the various health determinants. However, most previous studies investigate a single dimension of population health using linear models, failing to capture the ...
Zhiyuan Wei +2 more
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Multinomial Logit Models with Implicit Variable Selection [PDF]
, 2010 Multinomial logit models which are most commonly used for the modeling of unordered multi-category responses are typically restricted to the use of few predictors. In the high-dimensional case maximum likelihood estimates frequently do not exist. In this
Tutz, Gerhard, Zahid, Faisal Maqbool
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SLOPE - Adaptive variable selection via convex optimization [PDF]
, 2015 We introduce a new estimator for the vector of coefficients $\beta$ in the linear model $y=X\beta+z$, where $X$ has dimensions $n\times p$ with $p$ possibly larger than $n$. SLOPE, short for Sorted L-One Penalized Estimation, is the solution to \[\min_{b\
Berg, Ewout van den +4 more
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