Results 291 to 300 of about 24,713,244 (334)

Classification Uncertainty of Multiple Imputed Data

2015 IEEE Symposium Series on Computational Intelligence, 2015
Every classification model contains uncertainty. This uncertainty can be distributed evenly or into certain areas of feature space. In regular classification tasks, the uncertainty can be estimated from posterior probabilities. On the other hand, if the data set contains missing values, not all classifiers can be used directly.
Tuomo Alasalmi, Heli Koskimäki, Jaakko Suutala, Juha Röning   +3 more
openaire   +1 more source

A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation

Transportation Research Part C: Emerging Technologies, 2019
The missing data problem is inevitable when collecting traffic data from intelligent transportation systems. Previous studies have shown the advantages of tensor completion-based approaches in solving multi-dimensional data imputation problems.
Xinyu Chen, Zhaocheng He, Lijun Sun
semanticscholar   +1 more source

An Experimental Survey of Missing Data Imputation Algorithms

IEEE Transactions on Knowledge and Data Engineering, 2023
Xiaoye Miao, Yangyang Wu, Lu Chen, Yunjun Gao, Jianwei Yin   +4 more
semanticscholar   +1 more source

A systematic review of generative adversarial imputation network in missing data imputation

Neural computing & applications (Print), 2023
Yuqing Zhang, Runtong Zhang, Butian Zhao
semanticscholar   +1 more source

Imputation and Missing Data

2017
The presence of missing data is a big challenge for statisticians, especially if the distribution of the missing values is not completely random. Analysis performed on datasets with missing data can lead to erroneous conclusions and significant bias in the results.
Amir Momeni, Matthew Pincus, Jenny Libien   +2 more
openaire   +1 more source

IMPUTING MISSING DATA

Journal of the American Academy of Child & Adolescent Psychiatry, 2004
Calvin D, Croy, Douglas K, Novins
openaire   +2 more sources

Imputation of Missing Data

2011
Below is a subset of data from a smoking cessation study for smokers newly diagnosed with cancer.Patients were assessed for anxiety and depression at baseline using the Hospital Anxiety and Depression Scale (Zigmond and Snaith 1983), at least 7 days before they were hospitalized for surgery.
Yuelin Li, Jonathan Baron
openaire   +1 more source

An Interactive Data Imputation System

2022
Yangyang Wu, Xiaoye Miao, Yuchen Peng, Lu Chen 0001, Yunjun Gao, Jianwei Yin   +5 more
openaire   +1 more source

[Imputation of missing data].

Nederlands tijdschrift voor geneeskunde, 2013
In medical research missing data are sometimes inevitable. Different missingness mechanisms can be distinguished: (a) missing completely at random; (b) missing by design; (c) missing at random, and (d) missing not at random. If participants with missing data are excluded from statistical analyses, this can lead to biased study results and loss of ...
Ralph C A, Rippe, Martin, den Heijer, Saskia, le Cessie   +2 more
openaire   +1 more source

Multiple imputation with missing data indicators

Statistical Methods in Medical Research, 2021
Lauren J Beesley, Irina Bondarenko, Allison W Kurian   +2 more
exaly