Results 81 to 90 of about 202,004 (267)
A Comparative Study on Missing Value Imputation Techniques in Machine Learning [PDF]
SHS Web of ConferencesHandling missing values is a crucial step in data preprocessing, as incomplete data can significantly impact model performance and overall data integrity.
Meng Haoyu
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Research & Politics, 2018 Dyadic data from the United Nations High Commissioner for Refugees (UNHCR) on the size of the global refugee population are widely used. However, for a large fraction of the refugee population, these data provide no information about refugees’ country of origin, which contributes to a high nominal rate of unreported values in the data. In this article,
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Systemic Extracerebral Atherosclerotic Burden and Dementia Risk After Incident Stroke
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Stroke survivors are at increased risk of dementia, but clinically accessible markers of risk heterogeneity remain limited. Previous studies have largely examined atherosclerotic disease in individual vascular beds rather than the overall burden of systemic extracerebral atherosclerosis.
Zhexuan Yu +4 more
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An Imputation Method for Missing Data Based on an Extreme Learning Machine Auto-Encoder
IEEE Access, 2018 This paper proposes an imputation method for missing data based on an extreme learning machine auto-encoder (ELM-AE). The imputation chooses a set of plausible values determined by ELM-AE and then substitutes the average of these plausible values for the
Cheng-Bo Lu, Ying Mei
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We consider the problem of reconstructing missing data on a smooth manifold from incomplete and nonuniform samples. While classical methods for manifold approximation typically assume quasi-uniform data, their performance deteriorates significantly in the presence of large gaps or holes. We propose a unified framework for manifold data imputation
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Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea +53 more
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Arthritis Care &Research, EarlyView.Objective This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).
Amanda M. Saracino +42 more
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Arthritis Care &Research, EarlyView.Objective This study aimed to investigate hand function trajectories over five years in primary hand osteoarthritis (OA). Additionally, determinants of baseline and longitudinal hand function were assessed. Methods A total of 538 patients with both baseline and five‐year study visits were analyzed.
Annemiek V. E. M. Olde Meule +4 more
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Associations of Rheumatoid Arthritis Disease Activity With Frailty Over Five Years of Follow‐up
Arthritis Care &Research, EarlyView.Objective To evaluate whether rheumatoid arthritis (RA) disease activity is associated with frailty both in cross‐section and longitudinally. Methods Participants within the Veterans Affairs Rheumatoid Arthritis (VARA) registry enrolled from 2003 to 2022 were included.
Courtney N. Loecker +14 more
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AnimalGenomic prediction has been widely applied to the pig industry and has greatly accelerated the progress of genetic improvement in pigs. With the development of sequencing technology and price reduction, more and more genotype imputation panels of pig ...
J. Sun +7 more
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