Results 51 to 60 of about 204,036 (213)

TREB: a BERT attempt for imputing tabular data imputation

CoRR
12 pages, 7 ...
Shuyue Wang, Wenjun Zhou, Han Jiang, Shuo Wang, Ren Zheng   +4 more
openaire   +2 more sources

Missing data imputation of MAGDAS-9’s ground electromagnetism with supervised machine learning and conventional statistical analysis models

Alexandria Engineering Journal, 2022
Data imputation studies include reconstruction or estimation of imperfect data gaps caused by system sensing failure, and non-responsive data transmission remains an open issue.
Muhammad Asraf H., Nur Dalila K.A., Nooritawati Md Tahir, Zatul Iffah Abd Latiff, Mohamad Huzaimy Jusoh, Yoshikawa Akimasa   +5 more
doaj   +1 more source

New logarithmic type imputation techniques in presence of measurement errors

Alexandria Engineering Journal, 2023
Several imputation techniques have been constructed to sort out the missing data issue. However, there are few papers that address the missing data issue in measurement error (ME).
Shashi Bhushan, Anoop Kumar, Shivam Shukla, M.E. Bakr, Yusra A. Tashkandy, Md. Moyazzem Hossain   +5 more
doaj   +1 more source

weIMPUTE: a user-friendly web-based genotype imputation platform

Frontiers in Genetics
BackgroundGenotype imputation is a critical preprocessing step in genome-wide association studies (GWAS), enhancing statistical power for detecting associated single nucleotide polymorphisms (SNPs) by increasing marker size.ResultsIn response to the ...
Mingliang Li, Mingliang Li, Zhuo Li, Zhuo Li, Zhuo Li, Defu Liu, Qi Li, Xiaodong Hu, Jun Yu, Jian Lin, Chunguang Bi, Guanshi Ye, Helong Yu, You Tang, You Tang, You Tang   +15 more
doaj   +1 more source

Missing-Data Handling Methods for Lifelogs-Based Wellness Index Estimation: Comparative Analysis With Panel Data

JMIR Medical Informatics, 2020
BackgroundA lifelogs-based wellness index (LWI) is a function for calculating wellness scores based on health behavior lifelogs (eg, daily walking steps and sleep times collected via a smartwatch).
Kim, Ki-Hun, Kim, Kwang-Jae
doaj   +1 more source

Feature Based Multivariate Data Imputation [PDF]

, 2019
We investigate a new multivariate data imputation approach for dealing with variety of types of missingness. The proposed approach relies on the aggregation of the most suitable methods from a multitude of imputation techniques, adjusted to each feature of the dataset.
Alessio Petrozziello, Ivan Jordanov
openaire   +2 more sources

Multiple imputation for handling missing outcome data when estimating the relative risk

BMC Medical Research Methodology, 2017
Background Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk.
Thomas R. Sullivan, Katherine J. Lee, Philip Ryan, Amy B. Salter   +3 more
doaj   +1 more source

Discrete models for data imputation

Discrete Applied Mathematics, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

A method for increasing the robustness of multiple imputation [PDF]

, 2012
Missing data are common wherever statistical methods are applied in practice. They present a problem in that they require that additional assumptions be made about the mechanism leading to the incompleteness of the data.
Kenward, Michael G., Kenward, Michael G, Rhian M. Daniel, Daniel, Rhian M, Daniel, Rhian, Michael G. Kenward   +5 more
core   +1 more source

Manifold Data Imputation

CoRR
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.
openaire   +2 more sources