MLR3中的额外学习者

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想要改进此问题吗？更新该问题，因此它仅针对一个问题编辑此帖子。

闭合 2年前。

Answer 1

过滤此 list by class“ regr”学习者对于回归问题是可以避免的。

要初始化学习者，例如“ regr.kknn” do

# (1) mlr3 learners 
# install.packages("mlr3learners")
library(mlr3learners) 
#> Loading required package: mlr3
#mlr_learners

# (2) extra leaners
# remotes::install_github("mlr-org/mlr3extralearners")
library(mlr3extralearners)
regr_kknn = lrn("regr.kknn")
#> Warning: Package 'kknn' required but not installed for Learner 'regr.kknn'
print(regr_kknn)
#> <LearnerRegrKKNN:regr.kknn>
#> * Model: -
#> * Parameters: k=7
#> * Packages: mlr3, mlr3learners, kknn
#> * Predict Type: response
#> * Feature types: logical, integer, numeric, factor, ordered
#> * Properties: -

^{在2022-05-06创建的}

​/mlr3book.mlr-org.com/“ rel =“ nofollow noreferrer”> mlr3 book 。

关于您的第二个问题，我认为{mlr3}不会单独实现学习者。相反，它依靠多个库。这可能就是为什么regr.randomforest和regr.ranger可用的原因。