scikit-learn参考请求：树的特征重要性

Question

我试图了解如何计算回归树（及其整体对应物）的特征重要性。我正在查看compute_feature_importances中函数/sklearn/tree/_tree.pyx的源代码，并且不能完全遵循逻辑 - 并且没有引用。

对不起，这可能是一个非常基本的问题，但我找不到一个很好的文献参考，我希望有人可以指出我正确的方向，或快速解释代码，以便我可以继续挖掘。

由于

Answer 1

引用位于文档而不是代码中：

`feature_importances_` : array of shape = [n_features]
    The feature importances. The higher, the more important the
    feature. The importance of a feature is computed as the (normalized)
    total reduction of the criterion brought by that feature.  It is also
    known as the Gini importance [4]_.

.. [4] L. Breiman, and A. Cutler, "Random Forests",
       http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm