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 ------------------------------------------------------------------------------ Don't Limit Your Business. Reach for the Cloud. GigeNET's Cloud Solutions provide you with the tools and support that you need to offload your IT needs and focus on growing your business. Configured For All Businesses. Start Your Cloud Today. https://www.gigenetcloud.com/ _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
