Library Header Image
LSE Research Online LSE Library Services

A new imputation method for incomplete binary data

Subasi, Munevver Mine, Subasi, Ersoy, Anthony, Martin and Hammer, Peter L. (2012) A new imputation method for incomplete binary data. In: International Symposium on Artificial Intelligence and Mathematics, 2012-01-09 - 2012-01-11, Fort Lauderdale FL, United States. (Submitted)

Full text not available from this repository.


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 that employs a “similarity measure”. We compare experimentally the performance of our technique with ones based on the usual Hamming distance measure and multiple imputation.

Item Type: Conference or Workshop Item (Paper)
Official URL:
Additional Information: © 2012 The Authors
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
Date Deposited: 11 Jul 2012 10:39
Last Modified: 15 Sep 2023 08:30

Actions (login required)

View Item View Item