technologies. We integrate patent big data for technological integration and use text mining, boosting, and ensemble for integrated … technologies and analyze the integrated patent data using regression trees, random forest, extreme gradient boosting, and ensemble …

based on the ideas of mixed models. Specifically, we propose a semiparametric mixed model with boosting to recover the …

variables and the problems of selection of smoothing parameters. Generalized additive model boosting circumvents these problems …

of estimates. The present paper investigates several approaches to combining ridge regression with boosting techniques … the usual ridge estimator. In partial boosting only part of the regression parameters are reestimated within one step of … continuous response variables as well as in the case of generalized linear models. In a simulation study boosting procedures for …

is likelihood based boosting. Boosting originates in the machine learning community where it has been proposed as a … technique to improve classification procedures by combining estimates with reweighted observations. Likelihood based boosting is … a general method which may be seen as an extension of L2 boost. In additive mixed models the advantage of boosting …

precise convergence rates for satellite gradiometry, L2-boosting, and errors in variable problems. …

supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …

This paper looks into the ’fine print’ of boosting for economic forecasting. By using German industrial production for … selected by the boosting algorithm over time and four different forecasting horizons. It turns out that a number of hard … that never get chosen by the boosting approach at all. …