Stacked regressions

Efficient parallel algorithms for computing all possible subset regression models are proposed. The algorithms are based on the dropping columns method that generates a regression tree. The properties of the tree are exploited in order to provide an ...

With a simple transformation, the ordinary least squares objective can yield a family of modified ridge regressions which outperforms the regular ridge model. These models have more stable coefficients and a higher quality of fit with the growing ...

Stacking is a widely used technique for combining classifiers and improving prediction accuracy. Early research in Stacking showed that selecting the right classifiers, their parameters and the meta-classifiers was a critical issue. Most of the research ...