Carousel Greedy Algorithms for Feature Selection in Linear Regression

Carousel Greedy Algorithms for Feature Selection in Linear Regression

Blog Article

The carousel greedy algorithm (CG) was proposed several years ago as a generalized greedy algorithm.In this paper, we implement CG to solve linear regression problems with a cardinality constraint on the number of truvisionhealthftp.com features.More specifically, we introduce a default version of CG that has several novel features.We compare its performance against stepwise regression and more sophisticated approaches using integer programming, and the results are encouraging.For popularfilm.blog example, CG consistently outperforms stepwise regression (from our preliminary experiments, we see that CG improves upon stepwise regression in 10 of 12 cases), but it is still computationally inexpensive.

Furthermore, we show that the approach is applicable to several more general feature selection problems.