Cookies?
Library Header Image
LSE Research Online LSE Library Services

A new imputation method for incomplete binary data

Subasi, Mine, Subasi, Ersoy, Anthony, Martin and Hammer, P.L. (2009) A new imputation method for incomplete binary data. RUTCOR research report (RRR 15-2009). RUTCOR, Rutgers University.

Full text not available from this repository.

Abstract

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 known. In this paper, we propose a new approach to the imputation of missing binary values. The technique we introduce employs a "similarity measure". We compare experimentally the performance of our technique with ones based on the usual Hamming distance measure and a more classical statistical technique.

Item Type: Monograph (Report)
Official URL: http://rutcor.rutgers.edu/2009.html
Additional Information: © 2009 RUTCOR, Rutgers University
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
Date Deposited: 09 Apr 2010 12:59
Last Modified: 15 Sep 2023 22:10
URI: http://eprints.lse.ac.uk/id/eprint/27608

Actions (login required)

View Item View Item