Error Localization for Erroneous Data: Continuous Data, Linear Constraints
Robert Garfinkel, Anand S. Kunnathur, Gunar E. Liepins · SIAM Journal on Scientific and Statistical Computing · 1988
Data gathered in surveys, questionnaires, and censuses often contain a significant proportion of errors. If each record that fails a set of constraints (edits) is to be corrected, a reasonable model is to find the smallest (cheapest) set of fields which can be changed to yield a passing record. The problem is solved for continuous data and linear constraints using both a cutting plane algorithm based on the set-covering approach and a heuristic based on the simplex method. Extensive computational results are given.