支持多种解释方法:1.特征重要性(Feature Importance);2. 部分依赖图(Partial Dependence Plots, PDPs);3. 累积局部效应图(Accumulated Local Effects, ALEs); 4. Shapley值(Shapley Values);4. 模型诊断工具,如残差分析 相关拓展包:1. DALEXtra:扩展了DALEX,支持与更多的机器学习框架(如H2O、Keras、PyTorch)无缝...
力图(Force Plot):类似瀑布图的另一种表示方法,更注重特征贡献方向。 全局解释(Global Explanation):分析特征在整个数据集中的影响,例如:特征重要性图(Feature Importance):展示哪些特征对预测最重要。特征依赖图(Dependence Plot):探索特定特征的值如何影响预测结果。交互作用图(Interaction Plot):展示两个特征之间的交互...
The Shapley value is the average contribution of a feature value to the prediction in different coalitions. The Shapley value is NOT the difference in prediction when we would remove the feature from the model. Shapley value是针对feature value的而不是feature的(x1是该instance对应的x1的值,否则是平...
DeepSHAP结合了SHAP与DeepLIFT，将网络中较小组件的Shapley Value组合成整个网络的Shapley Value。我们可以通过局部分析（单样本分析）和全局分析（全样本分析）来看SHAP图。局部分析以预测值均值base_value为起点，全局分析对全部样本上的Shapley Value进行加和/平均，即可得到feature importance。
Other than the model importnaces given by RGF I would like to verify with permutation feature importance (scikit-learn) and/or with shapely values (shap package). But I can not do either, please help. Environment Info ACSVCPORT: 17532 AL...
Problems with Shapley-value-based explanations as feature importance measures. In Proc. International Conference on Machine Learning 5491–5500 (PMLR, 2020). Sundararajan, M. & Najmi, A. The many Shapley values for model explanation. In Proc. International Conference on Machine Learning 9269–9278...
In this paper, we proposed a new Explainable Artificial Intelligence (XAI) method called ShapG (Explanations based on Shapley value for Graphs) for measuring feature importance. ShapG is a model-agnostic global explanation method. At the first stage, it defines an undirected graph based on the ...
Fig. 1: G-DeepSHAP estimates Shapley value feature attributions to explain a series of models using a baseline distribution. a Local feature attributions with G-DeepSHAP require explicands (samples being explained), a baseline distribution (samples being compared to), and a model that is comprise...
[4] Kumar, I. Elizabeth, Suresh Venkatasubramanian, Carlos Scheidegger, and Sorelle Friedler. "Problems with Shapley-Value-Based Explanations as Feature Importance Measures."Proceedings of the 37th International Conference on Machine Learning119 (July 2020): 5491–500....
Paper tables with annotated results for ShapG: new feature importance method based on the Shapley value