预处理后的名称特征重要性图 [英] Names features importance plot after preprocessing

问题描述

在构建模型之前，我会像这样缩放

Before building a model I make scaling like this

X = StandardScaler(with_mean = 0, with_std = 1).fit_transform(X)

并在构建特征重要性图之后

and after build a features importance plot

xgb.plot_importance(bst, color='red')
plt.title('importance', fontsize = 20)
plt.yticks(fontsize = 10)
plt.ylabel('features', fontsize = 20)

问题是，我们得到的不是特征名称，而是 f0、f1、f2、f3 等......如何返回功能的名称?

The problem is that instead of feature's names we get f0, f1, f2, f3 etc..... How to return feature's names?

谢谢

推荐答案

在预处理之前我们首先得到特征名称列表

first we get list of feature names before preprocessing

dtrain = xgb.DMatrix( X, label=y)
dtrain.feature_names

然后

bst.get_fscore()
mapper = {'f{0}'.format(i): v for i, v in enumerate(dtrain.feature_names)}
mapped = {mapper[k]: v for k, v in bst.get_fscore().items()}
mapped
xgb.plot_importance(mapped, color='red')

就这些

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