MLR随机森林多标签获取特征重要性

Question

我正在使用来自 mlr 包的 multilabel.randomForestSRC 学习器来解决多标签分类问题我想 return 变量重要性

getFeatureImportance函数return本期：

代码：

getFeatureImportance(mod)

错误：

Error in checkLearner(object$learner, props = "featimp") : 
Learner 'multilabel.randomForestSRC' must support properties 'featimp', but does not support featimp'

Answer 1

您可以使用 randomForestSRC::vimp 中的示例提取变量重要性：

library(mlr)
yeast = getTaskData(yeast.task)
labels = colnames(yeast)[1:14]
yeast.task = makeMultilabelTask(id = "multi", data = yeast, target = labels)
lrn.rfsrc = makeLearner("multilabel.randomForestSRC")
mod2 = train(lrn.rfsrc, yeast.task)

vi =randomForestSRC::vimp(mod2$learner.model)
plot(vi,m.target ="label2")

MLR随机森林多标签获取特征重要性

MLR random forest multi label get feature importance

r

multilabel-classification

mlr