Symbolic regression in multicollinearity problems

In this paper the potential of GP-generated symbolic regression for alleviating multicollinearity problems in multiple regression is presented with a case study in an industrial setting. The main advantage of this approach is the potential to produce a simple and stable polynomial model in terms of the original variables. Categories and Subject Descriptors G.3. [Mathematics of Computing]: Probability and statistics– Correlation and regression analysis. General Terms: Experimentation. Keywords Multicollinearity, multiple regression, undesigned data

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Flor A. Castillo, Carlos M. Villa
• Keywords: GECCO 2005, GP-generated Symbolic Regression, Multicollinearity Problems, Multiple Regression