Bootstrapping and Multiple Imputation Ensemble Approaches for Missing Data

@article{Khan2018BootstrappingAM,
  title={Bootstrapping and Multiple Imputation Ensemble Approaches for Missing Data},
  author={Shehroz S. Khan and Amir Ahmad and Alex Mihailidis},
  journal={CoRR},
  year={2018},
  volume={abs/1802.00154}
}
Correspondence *Corresponding author Email: shehroz.khan@utoronto.ca Conflict of Interest: None Presence of missing values in a dataset can adversely affect the performance of a classifier. Single and Multiple Imputation are normally performed to fill in the missing values. In this paper, we present several variants of combining single and multiple… CONTINUE READING