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math.ST updates on arXiv.org

What is Learnable in Valiant's Theory of the Learnable? 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$L_2$ boosting in kernel regression
B. U. Park, Y. K. Lee, S. Ha · 2009-09-04 · via math.ST updates on arXiv.org

In this paper, we investigate the theoretical and empirical properties of $L_2$ boosting with kernel regression estimates as weak learners. We show that each step of $L_2$ boosting reduces the bias of the estimate by two orders of magnitude, while it does not deteriorate the order of the variance. We illustrate the theoretical findings by some simulated examples. Also, we demonstrate that $L_2$ boosting is superior to the use of higher-order kernels, which is a well-known method of reducing the bias of the kernel estimate.

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