我进行了练习,需要训练线性回归模型并获得有关该模型的一些信息:
使用lm函数创建模型很容易,因此我可以用摘要(修改)。
mod <- lm(cars$height ~ ., data = cars)
[summary()-MEthod返回所有内容:r平方,系数,p值,重要性...
但是当我训练我的模型像:
library(mlr)
lrn = makeLearner("regr.ksvm")
mod = train(learner = lrn, task = task)
pred = predict(object = mod, newdata = test)
performance(pred = pred, measures = list(mse, arsq))
我只是得到mse和r-squareZd。如何获得其他信息,例如重要性,重要变量...是否有机会获得此Mod?
感谢您的帮助
library(mlr)
#> Loading required package: ParamHelpers
#> 'mlr' is in maintenance mode since July 2019. Future development
#> efforts will go into its successor 'mlr3' (<https://mlr3.mlr-org.com>).
lrn = makeLearner("regr.lm")
mod = train(learner = lrn, task = bh.task)
getLearnerModel(mod)
#>
#> Call:
#> stats::lm(formula = f, data = d)
#>
#> Coefficients:
#> (Intercept) crim zn indus chas1 nox
#> 3.646e+01 -1.080e-01 4.642e-02 2.056e-02 2.687e+00 -1.777e+01
#> rm age dis rad tax ptratio
#> 3.810e+00 6.922e-04 -1.476e+00 3.060e-01 -1.233e-02 -9.527e-01
#> b lstat
#> 9.312e-03 -5.248e-01
reprex package(v0.3.0.9001)于2020-01-15创建