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Support Vector Regression Machines

H. Drucker,C. Burges,2 Authors,V. Vapnik

1996 · DBLP: conf/nips/DruckerBKSV96
Neural Information Processing Systems · 5,299 Citations

TLDR

This work compares support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space and expects that SVR will have advantages in high dimensionality space because SVR optimization does not depend on the dimensionality of the input space.