Re: [R] re gression trees: mean square vs. absolute errors

From: David Katz <>
Date: Tue, 25 Mar 2008 12:35:29 -0700 (PDT)

You need to think through the application of your model. Is it more important to get more cases classified correctly, or to avoid "bigger" errors versus a probability prediction? You should optimize your choice of a loss function so that it is appropriate to the way in which the model will be used.

lubaroz wrote:
> Hi,
> I am working with CART regression now to predict a probability; the
> response is binary. Could anyone tell me in which cases it is better to
> use mean square error for splitting nodes and when mean absolute error
> should be preferred.
> I am now using the default (MSE) version and I can see that the obtained
> optimal tree is very different from the tree with the least mean absolute
> error.
> Thanks in advance,
> Luba

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