支持向量机
维数之咒
回归
人工智能
回归分析
计算机科学
相关向量机
特征向量
局部回归
多项式回归
机器学习
模式识别(心理学)
数学
统计
作者
Harris Drucker,Christopher J. C. Burges,Linda Kaufman,Alex Smola,Vladimir Vapnik
摘要
A new regression technique based on Vapnik's concept of support vectors is introduced. We compare support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space. On the basis of these experiments, it is expected that SVR will have advantages in high dimensionality space because SVR optimization does not depend on the dimensionality of the input space.
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