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

[David Katz]

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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