Citation | Year | Publisher | Article | Journal/conference/book chapter |
---|---|---|---|---|
[153] | 2020 | Applied Science | Missing value imputation in stature estimation by learning algorithms using anthropometric data: a comparative study | Multidisciplinary Digital Publishing Institute |
[139] | 2020 | Applied Science | Evaluating machine learning classification using sorted missing percentage technique based on missing data | Multidisciplinary Digital Publishing Institute |
[154] | 2020 | Biometrical Journal | Multiple imputation methods for handling missing values in longitudinal studies with sampling weights: comparison of methods implemented in Stata | Wiley Online Library |
[155] | 2019 | Applied Artificial Intelligence | Comparison of performance of data imputation methods for numeric dataset | Taylor and Francis |
[8] | 2006 | Elsevier | A gentle introduction to imputation of missing values | Journal of clinical epidemiology |
[127] | 2017 | Elsevier | Adjusted weight voting algorithm for random forests in handling missing values | Pattern Recognition |
[60] | 2017 | Elsevier | kNN-IS: an Iterative Spark-based design of the k-Nearest Neighbors classifier for big data | Knowledge-Based Systems |
[156] | 2021 | Elsevier | Ground PM2. 5 prediction using imputed MAIAC AOD with uncertainty quantification | Environmental Pollution |
[157] | 2021 | Elsevier | A neural network approach for traffic prediction and routing with missing data imputation for intelligent transportation system | Expert Systems with Applications |
[158] | 2021 | Elsevier | Handling complex missing data using random forest approach for an air quality monitoring dataset: a case study of Kuwait environmental data (2012 to 2018) | Multidisciplinary Digital Publishing Institute |
[159] | 2021 | Elsevier | HA new method of data missing estimation with FNN-based tensor heterogeneous ensemble learning for internet of vehicle | Neurocomputing |
[111] | 2006 | IEEE | Ensemble based systems in decision making | IEEE Circuits and systems magazine |
[160] | 2010 | IEEE | Missing value estimation for mixed-attribute data sets | IEEE Transactions on Knowledge and Data Engineering |
[161] | 2014 | IEEE | Modeling and optimization for big data analytics:(statistical) learning tools for our era of data deluge | IEEE Signal Processing Magazine |
[2] | 2014 | IEEE | Handling missing data problems with sampling methods | 2014 International Conference on Advanced Networking Distributed Systems and Applications |
[123] | 2018 | IEEE | An imputation method for missing data based on an extreme learning machine auto-encoder | IEEE ACCESS |
[162] | 2018 | IEEE | A data imputation model in phasor measurement units based on bagged averaging of multiple linear regression | IEEE ACCESS |
[163] | 2018 | IEEE | Missing network data a comparison of different imputation methods | 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) |
[164] | 2018 | IEEE | MIAEC: missing data imputation based on the evidence chain | IEEE ACCESS |
[165] | 2018 | IEEE | A survey on data imputation techniques: water distribution system as a use case | IEEE ACCESS |
[166] | 2019 | IEEE | Missing values estimation on multivariate dataset: comparison of three type methods approach | International Conference on Information and Communications Technology (ICOIACT) |
[122] | 2019 | IEEE | A novel algorithm for missing data imputation on machine learning | 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) |
[167] | 2020 | IEEE | Approaches to dealing with missing data in railway asset management | IEEE ACCESS |
[168] | 2020 | IEEE | Traffic data imputation and prediction: an efficient realization of deep learning | IEEE ACCESS |
[169] | 2020 | IEEE | Iterative robust semi-supervised missing data imputation | IEEE ACCESS |
[170] | 2021 | IEEE | Missing network data a comparison of different imputation methods Neighborhood-aware autoencoder for missing value imputation | 2020 28th European Signal Processing Conference (EUSIPCO) |
[171] | 2021 | IEEE | Hybrid missing value imputation algorithms using fuzzy C-means and vaguely quantified rough set | IEEE Transactions on Fuzzy Systems |
[56] | 2016 | SAGE Publications | Multiple imputation in the presence of high-dimensional data | Statistical Methods in Medical Research |
[172] | 2020 | Sensors | A method for sensor-based activity recognition in missing data scenario | Multidisciplinary Digital Publishing Institute |
[31] | 2012 | Springer | Analysis of missing data | Missing data |
[65] | 2015 | Springer | CKNNI: an improved knn-based missing value handling technique | International Conference on Intelligent Computing |
[126] | 2015 | Springer | Missing data imputation by K nearest neighbours based on grey relational structure and mutual information | Applied Intelligence |
[63] | 2016 | Springer | Nearest neighbor imputation algorithms: a critical evaluation | BMC medical informatics and decision making |
[105] | 2017 | Springer | Multiple imputation and ensemble learning for classification with incomplete data | Intelligent and Evolutionary Systems |
[68] | 2018 | Springer | NS-kNN: a modified k-nearest neighbors approach for imputing metabolomics data | Metabolomics |
[136] | 2019 | Springer | Analysis of interpolation algorithms for the missing values in IoT time series: a case of air quality in Taiwan | The Journal of Super computing |
[39] | 2020 | Springer Open | SICE: an improved missing data imputation technique | Journal of Big Data |
[138] | 2020 | Springer | BEST: a decision tree algorithm that handles missing values | Computational Statistics |
[173] | 2020 | Springer | A new multi-view learning machine with incomplete data | Pattern Analysis and Applications |
[140] | 2021 | Springer | Multistage model for accurate prediction of missing values using imputation methods in heart disease dataset | Innovative Data Communication Technologies and Application |
[14] | 2021 | Springer | A new imputation method based on genetic programming and weighted KNN for symbolic regression with incomplete data | Soft Computing |
[174] | 2021 | Springer | An exploration of online missing value imputation in non-stationary data stream | SN Computer Science |
[175] | 2021 | Springer | Data imputation in wireless sensor network using deep learning techniques | Data Analytics and Management |
[176] | 2020 | Sustainable and Resilient Infrastructure | Handling incomplete and missing data in water network database using imputation methods | Taylor and Francis |