Results 51 to 60 of about 1,218,748 (261)
Missing Value Imputation with Unsupervised Backpropagation [PDF]
Computational Intelligence, 2014 AbstractMany data mining and data analysis techniques operate on dense matrices or complete tables of data. Real‐world data sets, however, often contain unknown values. Even many classification algorithms that are designed to operate with missing values still exhibit deteriorated accuracy.
Michael S. Gashler +3 more
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Clustering-based Missing Value Filling Method for Continuous Data [PDF]
Jisuanji gongcheng, 2019 In big data applications,most modeling methods are based on a complete data set,but data missing in the data acquisition process or storing process tend to result in failure to modeling.Therefore,a clustering-based recursive filling method is proposed ...
LI Guohe, YANG Shaowei, WU Weijiang, ZHENG Yifeng
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction This final analysis of a multicenter, prospective postmarketing surveillance study evaluated the safety of daprodustat in patients with chronic kidney disease anemia in routine clinical practice in Japan. Methods Patients who initiated daprodustat between September 2020 and July 2022 were registered.
Tadao Akizawa +7 more
wiley +1 more source
Effect of Imputation Methods in the Classifier Performance
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2019 Missingvalues in a data set present an important problem for almost any traditionaland modern statistical method, since most of these methods were developed underthe assumption that the data set was complete.
Pinar Cihan +2 more
doaj
The Hidden Value of Missing Genotypes [PDF]
Molecular Biology and Evolution, 2006 Robotic systems allow vast genetic data sets to be generated automatically with little manual input, raising questions about accuracy. To test whether errors occur randomly, I used the frequencies of missing genotypes in a large human data set to construct a population tree.
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Japan has one of the highest dialysis prevalence rates worldwide and a shrinking, aging population. Whether dialysis burden has entered a sustained post‐peak phase or whether recent declines partly reflect pandemic‐related disruptions remains uncertain.
Hatice Şahin +2 more
wiley +1 more source
JOIV: International Journal on Informatics VisualizationDue to the discrepancy in resolution between existing global climate model output and the resolution required by decision-makers, there is a persistent need for climate downscaling.
Raghdah Rasyidah Abdul Rashid +6 more
doaj +1 more source
Missing Values in Multivariate Analysis
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1975 Summary This paper presents computational results for some alternative methods of analysing multivariate data with missing values. We recommend an algorithm due to Orchard and Woodbury (1972), which gives an estimator that is maximum likelihood when the data come from a multivariate normal population.
Beale, E. M. L., Little, R. J. A.
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito +7 more
wiley +1 more source