A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Subset selection by Mallows' Cp: A mixed integer programming approach
2015
Expert systems with applications
This paper concerns a method of selecting the best subset of explanatory variables for a linear regression model. Employing Mallows' C p as a goodness-of-fit measure, we formulate the subset selection problem as a mixed integer quadratic programming problem. Computational results demonstrate that our method provides the best subset of variables in a few seconds when the number of candidate explanatory variables is less than 30. Furthermore, when handling datasets consisting of a large number of
doi:10.1016/j.eswa.2014.07.056
fatcat:buyje3xkzvfonhizjwxsxw26fa