Dataset of the paper “Variable selection for linear regression in large databases: exact methods” Applied Intelligence, 51(6), 3736-3756

The problem consists in selecting a small subset of independent variables that can perform the prediction task optimally. This problem has a wide range of applications.

One important type of application is the design of composite indicators in various areas (sociology and economics, for example). Other important applications of variable selection in linear regression can be found in fields such as chemometrics, genetics, and climate prediction, among many others. For this problem, we propose a Branch & Bound method.