Why does this help in the case of noise
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In building a regression tree, instead of the mean we can use the median, and instead of minimizing the squared error we can minimize the absolute error. Why does this help in the case of noise?
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In building a regression tree, instead of the mean we can use the median, and instead of minimizing the squared error. Why does this help in the case of noise?
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