2020
DOI: 10.1016/j.socnet.2020.02.005
|View full text |Cite
|
Sign up to set email alerts
|

Imputation of attributes in networked data using Bayesian autocorrelation regression models

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 35 publications
0
2
0
Order By: Relevance
“…There are some straightforward imputation models, including average imputation models, k-nearest neighbor (KNN) models and regression analysis (El Esawey, 2018). In addition, some complex algorithms are used for imputation, such as K-means, Bayesian networks, SVM and RF (Spinelli et al, 2020;Roeling et al, 2020;Sefidian et al, 2019;Tang et al, 2017;Zhang et al, 2009). These machine learning algorithms are more accurate, but the calculations are more complex (Kaplan and Yavuz, 2019).…”
Section: Prediction and Data Imputationmentioning
confidence: 99%
See 1 more Smart Citation
“…There are some straightforward imputation models, including average imputation models, k-nearest neighbor (KNN) models and regression analysis (El Esawey, 2018). In addition, some complex algorithms are used for imputation, such as K-means, Bayesian networks, SVM and RF (Spinelli et al, 2020;Roeling et al, 2020;Sefidian et al, 2019;Tang et al, 2017;Zhang et al, 2009). These machine learning algorithms are more accurate, but the calculations are more complex (Kaplan and Yavuz, 2019).…”
Section: Prediction and Data Imputationmentioning
confidence: 99%
“…In addition, some complex algorithms are used for imputation, such as K -means, Bayesian networks, SVM and RF (Spinelli et al. , 2020; Roeling et al. , 2020; Sefidian et al.…”
Section: Literature Reviewmentioning
confidence: 99%