Hi Sebastian,

Both terminology are in fact strictly equivalent for regression. See
e.g. page 46 of http://arxiv.org/abs/1407.7502

Best,
Gilles

On 9 July 2015 at 18:56, Sebastian Raschka <se.rasc...@gmail.com> wrote:
> Hi, all,
>
> sorry, but I have another question regarding the terminology in the 
> documentation.
>
> In the DecisionTreeRegressor's documentation at
> http://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html#sklearn.tree.DecisionTreeRegressor
> is says
>
> criterion : string, optional (default=”mse”)
> The function to measure the quality of a split. The only supported criterion 
> is “mse” for the mean squared error.
>
> However, I am wondering if the impurity measure is truly the MSE or if it is 
> the variance of the nodes (since the wikipedia link on that page refers to 
> the "variance reduction" algorithm)? Here, I think of MSE as the average of 
> squared deviations of the predictions from the true values, whereas variance 
> would be the average of squared deviation of the observations from the sample 
> mean of a node.
>
> Best,
> Sebastian
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