Improvd downward branch and bound algorithm for regression variable selection
Updated 19 Feb 2013
Subset (feature) selection for least squares regression is a common problem, which is combinartorial, hence is computationally NP hard. This code provides a tool using the improved downward branch and bound approach to solve this problem efficiently. One of the applications of this algorithm is to select globally optimal controlled variables for self-optimizing control.
Yi Cao (2023). Improvd downward branch and bound algorithm for regression variable selection (https://www.mathworks.com/matlabcentral/fileexchange/40357-improvd-downward-branch-and-bound-algorithm-for-regression-variable-selection), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Regression > Model Building and Assessment >
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!
Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.