Visualizations for mlr3learners::mlr_learners_classif.glmnet, mlr3learners::mlr_learners_regr.glmnet, mlr3learners::mlr_learners_classif.cv_glmnet and mlr3learners::mlr_learners_regr.cv_glmnet using the package ggfortify.

Note that learner-specific plots are experimental and subject to change.

# S3 method for LearnerClassifCVGlmnet
autoplot(object, ...)

# S3 method for LearnerClassifGlmnet
autoplot(object, ...)

# S3 method for LearnerRegrCVGlmnet
autoplot(object, ...)

# S3 method for LearnerRegrGlmnet
autoplot(object, ...)

Arguments

object

(mlr3learners::LearnerClassifGlmnet | mlr3learners::LearnerRegrGlmnet | mlr3learners::LearnerRegrCVGlmnet | mlr3learners::LearnerRegrCVGlmnet).

...

(any): Additional arguments, passed down to ggparty::autoplot.party().

Value

ggplot2::ggplot() object.

References

Tang Y, Horikoshi M, Li W (2016). “ggfortify: Unified Interface to Visualize Statistical Result of Popular R Packages.” The R Journal, 8(2), 474--485. doi: 10.32614/RJ-2016-060 .

Examples

if (FALSE) { library(mlr3) library(mlr3viz) library(mlr3learners) # classification task = tsk("sonar") learner = lrn("classif.glmnet") learner$train(task) autoplot(learner) # regression task = tsk("mtcars") learner = lrn("regr.glmnet") learner$train(task) autoplot(learner) }