155 related articles for article (PubMed ID: 34833670)
1. An Ensemble Method for Missing Data of Environmental Sensor Considering Univariate and Multivariate Characteristics.
Choi C; Jung H; Cho J
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833670
[TBL] [Abstract][Full Text] [Related]
2. Selection of statistical technique for imputation of single site-univariate and multisite-multivariate methods for particulate pollutants time series data with long gaps and high missing percentage.
K P; Shakya KS; Kumar P
Environ Sci Pollut Res Int; 2023 Jun; 30(30):75469-75488. PubMed ID: 37219777
[TBL] [Abstract][Full Text] [Related]
3. Advanced methods for missing values imputation based on similarity learning.
Fouad KM; Ismail MM; Azar AT; Arafa MM
PeerJ Comput Sci; 2021; 7():e619. PubMed ID: 34395861
[TBL] [Abstract][Full Text] [Related]
4. Robust imputation method with context-aware voting ensemble model for management of water-quality data.
Choi J; Lim KJ; Ji B
Water Res; 2023 Sep; 243():120369. PubMed ID: 37499538
[TBL] [Abstract][Full Text] [Related]
5. Deep Learning Approach for Imputation of Missing Values in Actigraphy Data: Algorithm Development Study.
Jang JH; Choi J; Roh HW; Son SJ; Hong CH; Kim EY; Kim TY; Yoon D
JMIR Mhealth Uhealth; 2020 Jul; 8(7):e16113. PubMed ID: 32445459
[TBL] [Abstract][Full Text] [Related]
6. Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data.
Mir AA; Kearfott KJ; Çelebi FV; Rafique M
PLoS One; 2022; 17(1):e0262131. PubMed ID: 35025953
[TBL] [Abstract][Full Text] [Related]
7. Imputation methods for addressing missing data in short-term monitoring of air pollutants.
Hadeed SJ; O'Rourke MK; Burgess JL; Harris RB; Canales RA
Sci Total Environ; 2020 Aug; 730():139140. PubMed ID: 32402974
[TBL] [Abstract][Full Text] [Related]
8. An Approach towards Increasing Prediction Accuracy for the Recovery of Missing IoT Data Based on the GRNN-SGTM Ensemble.
Tkachenko R; Izonin I; Kryvinska N; Dronyuk I; Zub K
Sensors (Basel); 2020 May; 20(9):. PubMed ID: 32375400
[TBL] [Abstract][Full Text] [Related]
9. Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018).
Alsaber AR; Pan J; Al-Hurban A
Int J Environ Res Public Health; 2021 Feb; 18(3):. PubMed ID: 33540610
[TBL] [Abstract][Full Text] [Related]
10. Comparison of imputation methods for missing production data of dairy cattle.
You J; Ellis JL; Adams S; Sahar M; Jacobs M; Tulpan D
Animal; 2023 Dec; 17 Suppl 5():100921. PubMed ID: 37659911
[TBL] [Abstract][Full Text] [Related]
11. Spatial imputation for air pollutants data sets via low rank matrix completion algorithm.
Liu X; Wang X; Zou L; Xia J; Pang W
Environ Int; 2020 Jun; 139():105713. PubMed ID: 32289585
[TBL] [Abstract][Full Text] [Related]
12. A Hybrid Missing Data Imputation Method for Batch Process Monitoring Dataset.
Gan Q; Gong L; Hu D; Jiang Y; Ding X
Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960379
[TBL] [Abstract][Full Text] [Related]
13. An efficient ensemble method for missing value imputation in microarray gene expression data.
Zhu X; Wang J; Sun B; Ren C; Yang T; Ding J
BMC Bioinformatics; 2021 Apr; 22(1):188. PubMed ID: 33849444
[TBL] [Abstract][Full Text] [Related]
14. A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems.
Zhang L
Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33096719
[TBL] [Abstract][Full Text] [Related]
15. A Pragmatic Ensemble Strategy for Missing Values Imputation in Health Records.
Batra S; Khurana R; Khan MZ; Boulila W; Koubaa A; Srivastava P
Entropy (Basel); 2022 Apr; 24(4):. PubMed ID: 35455196
[TBL] [Abstract][Full Text] [Related]
16. Evaluating Methods for Imputing Missing Data from Longitudinal Monitoring of Athlete Workload.
Benson LC; Stilling C; Owoeye OBA; Emery CA
J Sports Sci Med; 2021 Jun; 20(2):188-196. PubMed ID: 33948096
[TBL] [Abstract][Full Text] [Related]
17. An artificial neural network ensemble approach to generate air pollution maps.
Van Roode S; Ruiz-Aguilar JJ; González-Enrique J; Turias IJ
Environ Monit Assess; 2019 Nov; 191(12):727. PubMed ID: 31701254
[TBL] [Abstract][Full Text] [Related]
18. Bagging Ensemble of Multilayer Perceptrons for Missing Electricity Consumption Data Imputation.
Jung S; Moon J; Park S; Rho S; Baik SW; Hwang E
Sensors (Basel); 2020 Mar; 20(6):. PubMed ID: 32210112
[TBL] [Abstract][Full Text] [Related]
19. Imputation of Gene Expression Data in Blood Cancer and Its Significance in Inferring Biological Pathways.
Farswan A; Gupta A; Gupta R; Kaur G
Front Oncol; 2019; 9():1442. PubMed ID: 31970084
[No Abstract] [Full Text] [Related]
20. A deep learning technique for imputing missing healthcare data.
Phung S; Kumar A; Kim J
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():6513-6516. PubMed ID: 31947333
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]