Results 51 to 60 of about 3,737,276 (277)
Significance Analysis for Pairwise Variable Selection in Classification [PDF]
, 2014 The goal of this article is to select important variables that can distinguish one class of data from another. A marginal variable selection method ranks the marginal effects for classification of individual variables, and is a useful and efficient ...
Liu, Yufeng, Marron, J. S., Qiao, Xingye
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Gene selection: a Bayesian variable selection approach [PDF]
Bioinformatics, 2003 Abstract Selection of significant genes via expression patterns is an important problem in microarray experiments. Owing to small sample size and the large number of variables (genes), the selection process can be unstable. This paper proposes a hierarchical Bayesian model for gene (variable) selection.
Kyeong Eun, Lee +4 more
openaire +2 more sources
Gaussian Post-selection for Continuous Variable Quantum Cryptography [PDF]
, 2012 We extend the security proof for continuous variable quantum key distribution protocols using post selection to account for arbitrary eavesdropping attacks by employing the concept of an equivalent protocol where the post-selection is implemented as a ...
F. Grosshans +5 more
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Variable Selection by Perfect Sampling
EURASIP Journal on Advances in Signal Processing, 2002 Variable selection is very important in many fields, and for its resolution many procedures have been proposed and investigated. Among them are Bayesian methods that use Markov chain Monte Carlo (MCMC) sampling algorithms.
Huang Yufei, Djurić Petar M
doaj +1 more source
Communication and Language Profiles of Children Treated for Posterior Fossa Brain Tumors
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cognitive and language deficits are frequently reported sequelae of posterior fossa brain tumors (PFBT). Typically, delayed onset impedes prompt assessment and early intervention. This has devastating implications for quality of life.
Zara Sved +4 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The HIT network was established in 2000 to create a population‐based structure aiming to improve survival rates and reduce late effects for children with central nervous system (CNS) tumors by conducting comprehensive clinical trials.
Stefan Rutkowski +59 more
wiley +1 more source
Bayesian One-Sided Variable Selection
Multivariate Behavioral Research, 2020 This paper presents a novel Bayesian variable selection approach that accounts for the sign of the regression coefficients based on multivariate one-sided tests. We propose a truncated g prior to specify a prior distribution of coefficients with anticipated signs in a given model.
Xin Gu, Herbert Hoijtink, Joris Mulder
openaire +5 more sources
Variable selection with Random Forests for missing data [PDF]
, 2013 Variable selection has been suggested for Random Forests to improve their efficiency of data prediction and interpretation. However, its basic element, i.e.
Hapfelmeier, Alexander, Ulm, Kurt
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Characterizing stressful events reported by childhood cancer survivors experienced throughout the lifespan may help improve trauma‐informed care relevant to the survivor experience. Methods Participants included 2552 survivors (54% female; 34 years of age) and 469 community controls (62% female; 33 years of age) from the St.
Megan E. Ware +13 more
wiley +1 more source
Structured variable selection and estimation [PDF]
, 2009 In linear regression problems with related predictors, it is desirable to do variable selection and estimation by maintaining the hierarchical or structural relationships among predictors.
Joseph, V. Roshan, Yuan, Ming, Zou, Hui
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