Journal
DISCRETE APPLIED MATHEMATICS
Volume 159, Issue 10, Pages 1040-1047Publisher
ELSEVIER
DOI: 10.1016/j.dam.2011.01.024
Keywords
Imputation; Boolean similarity measure
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Funding
- European Community under PASCAL2 Network of Excellence
- NSF [NSF-IIS-0312953]
- NIH [NIH-002748-001, NIH-HL-072771-01]
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In data analysis problems where the data are represented by vectors of real numbers, it is often the case that some of the data-points will have missing values, meaning that one or more of the entries of the vector that describes the data-point is not observed. In this paper, we propose a new approach to the imputation of missing binary values. The technique we introduce employs a similarity measure introduced by Anthony and Hammer (2006) [1]. We compare experimentally the performance of our technique with ones based on the usual Hamming distance measure and multiple imputation. (C) 2011 Elsevier B.V. All rights reserved.
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