Imputation for the analysis of missing values and prediction of time series data

@article{Sridevi2011ImputationFT,
  title={Imputation for the analysis of missing values and prediction of time series data},
  author={S. Sridevi and Shyamsundar Rajaram and Chembian Parthiban and S. SibiArasan and C. Swadhikar},
  journal={2011 International Conference on Recent Trends in Information Technology (ICRTIT)},
  year={2011},
  pages={1158-1163}
}
Data preprocessing plays an important and critical role in the data mining process. Data preprocessing is required in order to improve the efficiency of an algorithm. This paper focuses on missing value estimation and prediction of time series data based on the historical values. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms like KNNimpute (K-Nearest Neighbours imputation), BPCA (Bayesian Principal Component… CONTINUE READING

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