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Impute vs. Ignore: Missing values for prediction
Citation
Zhang, Q and Rahman, A and D'Este, CE, Impute vs. Ignore: Missing values for prediction, Proceedings of the 2013 International Joint Conference on Neural Networks, 4-9 August 2013, Dallas, Texas, United States, pp. 1-8. ISBN 978-1-4673-6129-3 (2013) [Non Refereed Conference Paper]
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DOI: doi:10.1109/IJCNN.2013.6707014
Abstract
Sensor faults or communication errors can cause certain sensor readings to become unavailable for prediction purposes. In this paper we evaluate the performance of imputation techniques and techniques that ignore the missing values, in scenarios: (i) when values are missing only during prediction phase, and (ii) when values are missing during both the induction and prediction phase. We also investigated the influence of different scales of missingness on the performance of these treatments. The results can be used as a guideline to facilitate the choice of different missing value treatments under different circumstances.
Item Details
| Item Type: | Non Refereed Conference Paper |
|---|---|
| Keywords: | sensor faults, impute, ignore, prediction, missing value, |
| Research Division: | Information and Computing Sciences |
| Research Group: | Artificial intelligence |
| Research Field: | Knowledge representation and reasoning |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in the environmental sciences |
| UTAS Author: | D'Este, CE (Dr Claire D'Este) |
| ID Code: | 116719 |
| Year Published: | 2013 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2017-05-17 |
| Last Modified: | 2017-05-17 |
| Downloads: | 0 |
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