Results
Title

Method for Improving Gradient Boosting Learning Efficiency Based on Modified Loss Functions.

Authors

Korolev, N. S.; Senko, O. V.

Abstract

We consider a new method to improve the quality of training in gradient boosting as well as to increase its generalization performance based on the use of modified loss functions. In computational experiments, the possible applicability of this method to improve the quality of gradient boosting when solving various classification and regression problems on real data is shown.

Subjects

BOOSTING algorithms; DECISION trees; GENERALIZATION; MACHINE learning

Publication

Automation & Remote Control, 2022, Vol 83, Issue 12, p1935

ISSN

0005-1179

Publication type

Academic Journal

DOI

10.1134/S00051179220120074