Closed be-marc closed 3 years ago
Closes #157
learner = lrn("classif.rpart") learner$param_set$values$minsplit = to_tune(1, 10) parameters = tune(method = "random_search", task = tsk("pima"), learner = learner, resampling = rsmp ("holdout"), measure = msr("classif.ce"), term_evals = 50, batch_size = 10) learner$param_set$values = parameters
learner = lrn("classif.rpart") learner$param_set$values$minsplit = to_tune(1, 10) at = auto_tuner(method = "random_search", learner = learner, resampling = rsmp ("holdout"), measure = msr("classif.ce"), term_evals = 50, batch_size = 10) at$train(tsk("pima"))
learner = lrn("classif.rpart") learner$param_set$values$minsplit = to_tune(1, 10) rr = tune_nested(method = "random_search", task = tsk("pima"), learner = learner, inner_resampling = rsmp ("holdout"), outer_resampling = rsmp("cv", folds = 3), measure = msr("classif.ce"), term_evals = 50, batch_size = 10)
Closes #157