python - 如何在 SHAP 汇总图上绘制特定特征？

Question

我目前正在尝试在 SHAP 汇总图上绘制一组特定功能。但是，我正在努力寻找这样做所需的代码。

查看 Github 上的源代码时，summary_plot 函数似乎确实具有“特征”属性。但是，这似乎不能解决我的问题。

任何人都可以帮我绘制一组特定的功能，或者这在当前的 SHAP 代码中不是一个可行的选项。

Answer 1

一个可能的解决方案虽然很老套，但可能如下所示，例如在第 5 列中为单个特征绘制摘要图

shap.summary_plot(shap_values[:,5:6], X.iloc[:, 5:6])

Answer 2

我使用下面的代码重建 shap_value 以将您想要的功能包含到图中。

shap_values = explainer.shap_values(samples)[1]

vals = np.abs(shap_values).mean(0)
feature_importance = pd.DataFrame(
    list(zip(samples.columns, vals)),
    columns=["col_name", "feature_importance_vals"],
)
feature_importance.sort_values(
    by=["feature_importance_vals"], ascending=False, inplace=True
)

feature_importance['rank'] = feature_importance['feature_importance_vals'].rank(method='max',ascending=False)

missing_features = [
    i
    for i in columns_to_show
    if i not in feature_importance["col_name"][:20].tolist()
]
missing_index = []
for i in missing_features:
    missing_index.append(samples.columns.tolist().index(i))

missing_features_new = []
rename_col = {}
for i in missing_features:
    rank = int(feature_importance[feature_importance['col_name']==i]['rank'].values)
    missing_features_new.append('rank:'+str(rank)+' - '+i)
    rename_col[i] = 'rank:'+str(rank)+' - '+i

column_names = feature_importance["col_name"][:20].values.tolist() + missing_features_new

feature_index = feature_importance.index[:20].tolist() + missing_index

shap.summary_plot(
        shap_values[:, feature_index].reshape(
            samples.shape[0], len(feature_index)
        ),
            samples.rename(columns=rename_col)[column_names],
            max_display=len(feature_index),
        )

Answer 3

要仅绘制 1 个功能，请获取要检查功能列表的功能的索引

i = X.iloc[:,:].index.tolist().index('your_feature_name_here')
shap.summary_plot(shap_values[1][:,i:i+1], X.iloc[:, i:i+1])

要绘制您选择的特征，

your_feature_list = ['your_feature_1','your_feature_2','your_feature_3']
your_feature_indices = [X.iloc[:,:].index.tolist().index(x) for x in your_feature_list]
shap.summary_plot(shap_values[1][:,your_feature_indices], X.iloc[:, your_feature_indices])

随意将“your_feature_indices”更改为更短的变量名

如果您不进行二进制分类，请将 shap_values[1] 更改为 shap_values