docs: rewrite examples #305
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Thanks a lot already! Please make sure that the problems identified by rcmdcheck are addressed |
R/learner_gbm_regr_gbm.R
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| #' task = tsk("boston_housing") | ||
| #' | ||
| #' | ||
| #' # Train the learner on the training ids |
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this trains the task on all ids
R/learner_lme4_classif_glmer.R
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| #' # Define a Task | ||
| #' task = as_task_classif(faraway::toenail, target = "outcome") | ||
| #' | ||
| #' # Train the learner on the training ids |
R/learner_lme4_classif_glmer.R
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| #' print(learner) | ||
| #' | ||
| #' # Define a Task | ||
| #' task = as_task_classif(faraway::toenail, target = "outcome") |
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why not a standard task? is the faraway package available?
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I've tried some standard tests but they're not available for this learner, so I use the dataset in the example of function glmer instead.
R/learner_mboost_regr_gamboost.R
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| #' @examples | ||
| #' if (requireNamespace("mboost", quietly = TRUE)) { | ||
| #' # Define the Learner and set parameter values | ||
| #' |
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Note that you can (probably) use |
Co-authored-by: Sebastian Fischer <[email protected]>
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@Brandonxzl the CI is still not passing, please fix the line length :) |
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because the line length is still an issue, you can use |
R/learner_lme4_regr_lmer.R
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| @@ -15,7 +15,34 @@ | |||
| #' `r format_bib("bates2010lme4")` | |||
| #' | |||
| #' @template seealso_learner | |||
| #' @template example | |||
| #' @examples | |||
| #' if (requireNamespace(c("lme4", "faraway"), quietly = TRUE)) { | |||
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for building the task specified for this learner:
Define a Task
#' task = mlr3::as_task_regr(lme4::sleepstudy, target = "Reaction")
R/learner_mboost_regr_gamboost.R
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| #' learner$train(task) | ||
| #' | ||
| #' # print the model | ||
| #' print(learner$model) |
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If I can train a learner it should be possible to make predictions as well
R/learner_mboost_surv_gamboost.R
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| #' @template example | ||
| #' @examples | ||
| #' if (mlr3misc::require_namespaces(c("mlr3extralearners", "mboost", "pracma"), quietly = TRUE)) { | ||
| #' # Define the Learner and set parameter values |
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no parameter values are set.
Also, mboost and pracma are not required when I just want to construct the learner
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