Regression using decision tree Could you explain how to perform decision tree regression? How is it different from decision tree classification?

The main difference between classification and regression trees is that the target attribute (i.e. the variable you want to predict) of the classification tree is a continuous variable, while the target attribute of the decision tree is a categorical variable.
The main idea behind both is the same though.
For classifications, the metric used in the splitting process is an impurity index (e.g. Gini index) whilst for the regression tree, it is the Mean Squared Error.
