diff --git a/.Rbuildignore b/.Rbuildignore index ff5d83a..18a6d7e 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -23,3 +23,4 @@ .vscode ^kaggle$ ^oml_cache$ +^vignettes$ diff --git a/.gitignore b/.gitignore index 7c9632c..8a8a349 100644 --- a/.gitignore +++ b/.gitignore @@ -98,3 +98,4 @@ rsconnect/ .Rprofile kaggle/ README.html +inst/doc diff --git a/DESCRIPTION b/DESCRIPTION index eccd887..bf5cf3e 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -2,14 +2,14 @@ Package: mlr3automl Title: AutoML extention for 'mlr3' Version: 0.0.1 Authors@R: c( - person("Damir", "Pulatov", , "damirpolat@protonmail.com", role = c("cre", "aut")), - person("Marc", "Becker", , "marcbecker@posteo.de", role = "aut", - comment = c(ORCID = "0000-0002-8115-0400")), + person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"), + comment = c(ORCID = "0000-0002-8115-0400")), + person("Damir", "Pulatov", , "damirpolat@protonmail.com", role = "aut"), person("Baisu", "Zhou", , "baisu.zhou@outlook.com", role = "aut") ) Description: Flexible AutoML system for the 'mlr3' ecosystem. License: LGPL-3 -URL: https://github.com/mlr-org/mlr3automl +URL: https://github.com/mlr-org/mlr3automl https://mlr3automl.mlr-org.com BugReports: https://github.com/mlr-org/mlr3automl/issues Depends: mlr3 (>= 1.2.0.9000), @@ -35,6 +35,7 @@ Suggests: fastai, glmnet, kknn, + knitr, lgr, lightgbm, MASS, @@ -42,22 +43,24 @@ Suggests: mlr3extralearners, mlr3torch (>= 0.3.0.9000), mlr3viz, + quarto, ranger, redux, reticulate, + rmarkdown, rpart, testthat (>= 3.0.0), xgboost Remotes: catboost/catboost/catboost/R-package, eagerai/fastai, + mlr-org/bbotk, mlr-org/mlr3, mlr-org/mlr3extralearners, mlr-org/mlr3learners, mlr-org/mlr3mbo@so_config_6, mlr-org/mlr3torch, mlr-org/mlr3tuning, - mlr-org/bbotk, mlr-org/rush Config/testthat/edition: 3 Config/testthat/parallel: false diff --git a/R/Auto.R b/R/Auto.R index d2866b5..3724b8c 100644 --- a/R/Auto.R +++ b/R/Auto.R @@ -3,7 +3,7 @@ #' @description #' This class is the base class for all autos. #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @template param_id #' @template param_task @@ -14,6 +14,8 @@ #' @template param_large_data_set #' @template param_size #' @template param_devices +#' @template param_pv +#' @template param_graph #' #' @export Auto = R6Class("Auto", @@ -80,7 +82,7 @@ Auto = R6Class("Auto", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { stop("Abstract") }, @@ -154,6 +156,12 @@ Auto = R6Class("Auto", #' Get the search space for the learner. search_space = function(task) { private$.search_space + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + graph } ), diff --git a/R/AutoCatboost.R b/R/AutoCatboost.R index 2e65e6a..f8db213 100644 --- a/R/AutoCatboost.R +++ b/R/AutoCatboost.R @@ -1,6 +1,6 @@ #' @title Catboost Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R Auto.R #' #' @description #' Catboost auto. @@ -10,7 +10,12 @@ #' @template param_measure #' @template param_n_threads #' @template param_timeout +#' @template param_memory_limit +#' @template param_large_data_set +#' @template param_size #' @template param_devices +#' @template param_pv +#' @template param_graph #' #' @export AutoCatboost = R6Class("AutoCatboost", @@ -31,7 +36,7 @@ AutoCatboost = R6Class("AutoCatboost", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) @@ -52,10 +57,17 @@ AutoCatboost = R6Class("AutoCatboost", task_type = task_type) set_threads(learner, n_threads) - po("removeconstants", id = "catboost_removeconstants") %>>% + + graph = po("removeconstants", id = "catboost_removeconstants") %>>% po("colapply", id = "catboost_colapply", applicator = as.numeric, affect_columns = selector_type("integer")) %>>% po("removeconstants", id = "catboost_post_removeconstants") %>>% learner + + if (task$nrow * task$ncol > pv$large_data_size) { + graph = po("subsample", frac = 0.25, stratify = inherits(task, "TaskClassif"), use_groups = FALSE, id = "catboost_subsample") %>>% graph + } + + graph }, #' @description @@ -115,6 +127,14 @@ AutoCatboost = R6Class("AutoCatboost", "merror" # default ) } + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + if (task$nrow * task$ncol > pv$large_data_size) { + graph$param_set$set_values(catboost_subsample.frac = 1) + } } ), diff --git a/R/AutoExtraTrees.R b/R/AutoExtraTrees.R index fc93819..fe21d7b 100644 --- a/R/AutoExtraTrees.R +++ b/R/AutoExtraTrees.R @@ -1,17 +1,21 @@ #' @title Extra Trees Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Extra Trees auto. #' #' @template param_id -#' @template param_n_threads -#' @template param_timeout #' @template param_task #' @template param_measure +#' @template param_n_threads +#' @template param_timeout +#' @template param_memory_limit +#' @template param_large_data_set #' @template param_size #' @template param_devices +#' @template param_pv +#' @template param_graph #' #' @export AutoExtraTrees = R6Class("AutoExtraTrees", @@ -37,7 +41,7 @@ AutoExtraTrees = R6Class("AutoExtraTrees", #' @param measure ([mlr3::Measure]). #' @param n_threads (`numeric(1)`). #' @param timeout (`numeric(1)`). - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) @@ -53,13 +57,19 @@ AutoExtraTrees = R6Class("AutoExtraTrees", sample.fraction = 1) set_threads(learner, n_threads) - po("removeconstants", id = "extra_trees_removeconstants") %>>% + graph = po("removeconstants", id = "extra_trees_removeconstants") %>>% po("imputeoor", id = "extra_trees_imputeoor") %>>% po("fixfactors", id = "extra_trees_fixfactors") %>>% po("imputesample", affect_columns = selector_type(c("factor", "ordered")), id = "extra_trees_imputesample") %>>% po("collapsefactors", target_level_count = 40, id = "extra_trees_collapse") %>>% po("removeconstants", id = "extra_trees_post_removeconstants") %>>% learner + + if (task$nrow * task$ncol > pv$large_data_size) { + graph = po("subsample", frac = 0.25, stratify = inherits(task, "TaskClassif"), use_groups = FALSE, id = "extra_trees_subsample") %>>% graph + } + + graph }, #' @description @@ -70,6 +80,14 @@ AutoExtraTrees = R6Class("AutoExtraTrees", num_trees = 100 tree_size_bytes = task$nrow / 60000 * 1e6 ceiling((tree_size_bytes * num_trees) / 1e6) + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + if (task$nrow * task$ncol > pv$large_data_size) { + graph$param_set$set_values(extra_trees_subsample.frac = 1) + } } ) ) diff --git a/R/AutoFTTransformer.R b/R/AutoFTTransformer.R index c8cc74c..7da8a39 100644 --- a/R/AutoFTTransformer.R +++ b/R/AutoFTTransformer.R @@ -1,6 +1,6 @@ #' @title FTTransformer Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' FTTransformer auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoFTTransformer = R6Class("AutoFTTransformer", @@ -31,7 +32,7 @@ AutoFTTransformer = R6Class("AutoFTTransformer", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoFastai.R b/R/AutoFastai.R index b80585a..5087539 100644 --- a/R/AutoFastai.R +++ b/R/AutoFastai.R @@ -1,6 +1,6 @@ #' @title Fastai Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Fastai auto. @@ -13,6 +13,7 @@ #' @template param_memory_limit #' @template param_large_data_set #' @template param_devices +#' @template param_pv #' #' @export AutoFastai = R6Class("AutoFastai", @@ -49,7 +50,7 @@ AutoFastai = R6Class("AutoFastai", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoGlmnet.R b/R/AutoGlmnet.R index be600b1..ac68196 100644 --- a/R/AutoGlmnet.R +++ b/R/AutoGlmnet.R @@ -1,6 +1,6 @@ #' @title Glmnet Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Glmnet auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoGlmnet = R6Class("AutoGlmnet", @@ -30,7 +31,7 @@ AutoGlmnet = R6Class("AutoGlmnet", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoKknn.R b/R/AutoKknn.R index a4275b9..91ed867 100644 --- a/R/AutoKknn.R +++ b/R/AutoKknn.R @@ -1,6 +1,6 @@ #' @title Kknn Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Kknn auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoKknn = R6Class("AutoKknn", @@ -30,7 +31,7 @@ AutoKknn = R6Class("AutoKknn", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoLda.R b/R/AutoLda.R index 9d66116..e0bec1a 100644 --- a/R/AutoLda.R +++ b/R/AutoLda.R @@ -1,6 +1,6 @@ #' @title Lda Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Lda auto. @@ -14,6 +14,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoLda = R6Class("AutoLda", @@ -33,7 +34,7 @@ AutoLda = R6Class("AutoLda", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoLightgbm.R b/R/AutoLightgbm.R index e79b984..2c60eef 100644 --- a/R/AutoLightgbm.R +++ b/R/AutoLightgbm.R @@ -1,6 +1,6 @@ #' @title Lightgbm Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Lightgbm auto. @@ -10,7 +10,12 @@ #' @template param_measure #' @template param_n_threads #' @template param_timeout +#' @template param_memory_limit +#' @template param_large_data_set +#' @template param_size #' @template param_devices +#' @template param_pv +#' @template param_graph #' #' @export AutoLightgbm = R6Class("AutoLightgbm", @@ -30,7 +35,7 @@ AutoLightgbm = R6Class("AutoLightgbm", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) @@ -41,15 +46,19 @@ AutoLightgbm = R6Class("AutoLightgbm", device_type = if ("cuda" %in% devices) "gpu" else "cpu" - learner = lrn(sprintf("%s.lightgbm", task$task_type), + graph = lrn(sprintf("%s.lightgbm", task$task_type), id = "lightgbm", early_stopping_rounds = self$early_stopping_rounds(task), callbacks = list(cb_timeout_lightgbm(timeout * 0.9)), eval = self$internal_measure(measure, task), device_type = device_type) - set_threads(learner, n_threads) + set_threads(graph, n_threads) - learner + if (task$nrow * task$ncol > pv$large_data_size) { + graph = po("subsample", frac = 0.25, stratify = inherits(task, "TaskClassif"), use_groups = FALSE, id = "lightgbm_subsample") %>>% graph + } + + graph }, #' @description @@ -97,6 +106,15 @@ AutoLightgbm = R6Class("AutoLightgbm", "classif.logloss" = "multi_logloss", "multi_error") # default } + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + if (task$nrow * task$ncol > pv$large_data_size) { + graph$param_set$set_values(lightgbm_subsample.frac = 1) + } + graph$param_set$set_values(lightgbm.callbacks = NULL) } ), diff --git a/R/AutoMlp.R b/R/AutoMlp.R index 8108e99..36407d4 100644 --- a/R/AutoMlp.R +++ b/R/AutoMlp.R @@ -1,6 +1,6 @@ #' @title Mlp Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Mlp auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoMlp = R6Class("AutoMlp", @@ -31,7 +32,7 @@ AutoMlp = R6Class("AutoMlp", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoRanger.R b/R/AutoRanger.R index b019823..8195bfc 100644 --- a/R/AutoRanger.R +++ b/R/AutoRanger.R @@ -1,6 +1,6 @@ #' @title Ranger Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Ranger auto. @@ -10,8 +10,12 @@ #' @template param_measure #' @template param_n_threads #' @template param_timeout +#' @template param_memory_limit +#' @template param_large_data_set +#' @template param_size #' @template param_devices -#' +#' @template param_pv +#' @template param_graph #' #' @export AutoRanger = R6Class("AutoRanger", @@ -31,7 +35,7 @@ AutoRanger = R6Class("AutoRanger", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) @@ -42,13 +46,19 @@ AutoRanger = R6Class("AutoRanger", learner = lrn(sprintf("%s.ranger", task$task_type), id = "ranger") set_threads(learner, n_threads) - po("removeconstants", id = "ranger_removeconstants") %>>% + graph = po("removeconstants", id = "ranger_removeconstants") %>>% po("imputeoor", id = "ranger_imputeoor") %>>% po("fixfactors", id = "ranger_fixfactors") %>>% po("imputesample", affect_columns = selector_type(c("factor", "ordered")), id = "ranger_imputesample") %>>% po("collapsefactors", target_level_count = 100, id = "ranger_collapse") %>>% po("removeconstants", id = "ranger_post_removeconstants") %>>% learner + + if (task$nrow * task$ncol > pv$large_data_size) { + graph = po("subsample", frac = 0.25, stratify = inherits(task, "TaskClassif"), use_groups = FALSE, id = "ranger_subsample") %>>% graph + } + + graph }, #' @description @@ -62,6 +72,14 @@ AutoRanger = R6Class("AutoRanger", memory_size = (tree_size * num_trees) / 1e6 lg$info("Ranger memory size: %s MB", round(memory_size)) ceiling(memory_size) + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + if (task$nrow * task$ncol > pv$large_data_size) { + graph$param_set$set_values(ranger_subsample.frac = 1) + } } ), diff --git a/R/AutoResNet.R b/R/AutoResNet.R index e3264a7..96cc98d 100644 --- a/R/AutoResNet.R +++ b/R/AutoResNet.R @@ -1,6 +1,6 @@ #' @title ResNet Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' ResNet auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoResNet = R6Class("AutoResNet", @@ -30,7 +31,7 @@ AutoResNet = R6Class("AutoResNet", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoSvm.R b/R/AutoSvm.R index 5b49027..aa6289a 100644 --- a/R/AutoSvm.R +++ b/R/AutoSvm.R @@ -1,6 +1,6 @@ #' @title Svm Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Svm auto. @@ -11,6 +11,7 @@ #' @template param_n_threads #' @template param_timeout #' @template param_devices +#' @template param_pv #' #' @export AutoSvm = R6Class("AutoSvm", @@ -30,7 +31,7 @@ AutoSvm = R6Class("AutoSvm", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoTabpfn.R b/R/AutoTabpfn.R index 6a3beef..dda9d5e 100644 --- a/R/AutoTabpfn.R +++ b/R/AutoTabpfn.R @@ -1,6 +1,6 @@ #' @title Tabpfn Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Tabpfn auto. @@ -13,6 +13,7 @@ #' @template param_memory_limit #' @template param_large_data_set #' @template param_devices +#' @template param_pv #' #' @export AutoTabpfn = R6Class("AutoTabpfn", @@ -52,7 +53,7 @@ AutoTabpfn = R6Class("AutoTabpfn", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) diff --git a/R/AutoXgboost.R b/R/AutoXgboost.R index e786ca2..a66770d 100644 --- a/R/AutoXgboost.R +++ b/R/AutoXgboost.R @@ -1,6 +1,6 @@ #' @title Xgboost Auto #' -#' @include mlr_auto.R +#' @include mlr_auto.R Auto.R #' #' @description #' Xgboost auto. @@ -10,7 +10,12 @@ #' @template param_measure #' @template param_n_threads #' @template param_timeout +#' @template param_memory_limit +#' @template param_large_data_set +#' @template param_size #' @template param_devices +#' @template param_pv +#' @template param_graph #' #' @export AutoXgboost = R6Class("AutoXgboost", @@ -30,7 +35,7 @@ AutoXgboost = R6Class("AutoXgboost", #' @description #' Create the graph for the auto. - graph = function(task, measure, n_threads, timeout, devices) { + graph = function(task, measure, n_threads, timeout, devices, pv) { assert_task(task) assert_measure(measure) assert_count(n_threads) @@ -52,13 +57,19 @@ AutoXgboost = R6Class("AutoXgboost", learner$set_values(device = "cuda") } - po("removeconstants", id = "xgboost_removeconstants") %>>% + graph = po("removeconstants", id = "xgboost_removeconstants") %>>% po("imputeoor", id = "xgboost_imputeoor") %>>% po("fixfactors", id = "xgboost_fixfactors") %>>% po("imputesample", affect_columns = selector_type(c("factor", "ordered")), id = "xgboost_imputesample") %>>% po("encodeimpact", id = "xgboost_encode") %>>% po("removeconstants", id = "xgboost_post_removeconstants") %>>% learner + + if (task$nrow * task$ncol > pv$large_data_size) { + graph = po("subsample", frac = 0.25, stratify = inherits(task, "TaskClassif"), use_groups = FALSE, id = "xgboost_subsample") %>>% graph + } + + graph }, #' @description @@ -109,6 +120,15 @@ AutoXgboost = R6Class("AutoXgboost", "merror" # default ) } + }, + + #' @description + #' Modify the graph for the final model. + final_graph = function(graph, task, pv) { + if (task$nrow * task$ncol > pv$large_data_size) { + graph$param_set$set_values(xgboost_subsample.frac = 1) + } + graph$param_set$set_values(xgboost.callbacks = NULL) } ), diff --git a/R/train_auto.R b/R/train_auto.R index 5cf5587..702391c 100644 --- a/R/train_auto.R +++ b/R/train_auto.R @@ -42,7 +42,7 @@ train_auto = function(self, private, task) { error_config("All learners have no hyperparameters to tune. Combine with other learners.") } - branches = map(autos, function(auto) auto$graph(task, pv$measure, n_threads, pv$learner_timeout, pv$devices)) + branches = map(autos, function(auto) auto$graph(task, pv$measure, n_threads, pv$learner_timeout, pv$devices, pv)) graph_learner = as_learner(po("branch", options = names(branches)) %>>% gunion(unname(branches)) %>>% po("unbranch", options = names(branches)), clone = TRUE) @@ -139,15 +139,13 @@ train_auto = function(self, private, task) { # fit final model lg$info("Learner '%s' fits final model", self$id) - if (length(learners_with_validation)) { set_validate(graph_learner, NULL, ids = learners_with_validation) - # FIXME: remove this once we have a better way to handle this - graph_learner$param_set$values$xgboost.callbacks = NULL - graph_learner$param_set$values$lightgbm.callbacks = NULL } + graph_learner$param_set$set_values(.values = self$instance$result_learner_param_vals, .insert = FALSE) graph_learner$timeout = c(train = Inf, predict = Inf) + walk(autos, function(auto) auto$final_graph(graph_learner, task, pv)) graph_learner$train(task) list(graph_learner = graph_learner, instance = self$instance) diff --git a/man-roxygen/param_graph.R b/man-roxygen/param_graph.R new file mode 100644 index 0000000..fd2812e --- /dev/null +++ b/man-roxygen/param_graph.R @@ -0,0 +1,3 @@ +#' @param graph (`mlr3pipelines::GraphLearner`)\cr +#' Graph learner. + diff --git a/man-roxygen/param_pv.R b/man-roxygen/param_pv.R new file mode 100644 index 0000000..73a7570 --- /dev/null +++ b/man-roxygen/param_pv.R @@ -0,0 +1,3 @@ +#' @param pv (`list`)\cr +#' Parameter values. + diff --git a/man/Auto.Rd b/man/Auto.Rd index 9876eb5..0c66cd4 100644 --- a/man/Auto.Rd +++ b/man/Auto.Rd @@ -32,6 +32,7 @@ This class is the base class for all autos. \item \href{#method-Auto-design_default}{\code{Auto$design_default()}} \item \href{#method-Auto-design_set}{\code{Auto$design_set()}} \item \href{#method-Auto-search_space}{\code{Auto$search_space()}} +\item \href{#method-Auto-final_graph}{\code{Auto$final_graph()}} \item \href{#method-Auto-clone}{\code{Auto$clone()}} } } @@ -72,7 +73,7 @@ Creates a new instance of this \link[R6:R6Class]{R6} class. \subsection{Method \code{check()}}{ Check if the auto is compatible with the task. \subsection{Usage}{ -\if{html}{\out{
}}\preformatted{Auto$check(task, memory_limit = Inf, large_data_set = FALSE, devices)}\if{html}{\out{
}} +\if{html}{\out{
}}\preformatted{Auto$check(task, memory_limit = Inf, large_data_set = FALSE, devices, pv)}\if{html}{\out{
}} } \subsection{Arguments}{ @@ -88,6 +89,9 @@ Check if the auto is compatible with the task. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -98,7 +102,7 @@ Default is "cpu".} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
}}\preformatted{Auto$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
}} +\if{html}{\out{
}}\preformatted{Auto$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
}} } \subsection{Arguments}{ @@ -116,6 +120,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -210,6 +217,29 @@ Get the search space for the learner. } } \if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-Auto-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{Auto$final_graph(graph, task, pv)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
}} +} +} +\if{html}{\out{
}} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-Auto-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/AutoCatboost.Rd b/man/AutoCatboost.Rd index 209448f..78bdb90 100644 --- a/man/AutoCatboost.Rd +++ b/man/AutoCatboost.Rd @@ -16,6 +16,7 @@ Catboost auto. \item \href{#method-AutoCatboost-graph}{\code{AutoCatboost$graph()}} \item \href{#method-AutoCatboost-estimate_memory}{\code{AutoCatboost$estimate_memory()}} \item \href{#method-AutoCatboost-internal_measure}{\code{AutoCatboost$internal_measure()}} +\item \href{#method-AutoCatboost-final_graph}{\code{AutoCatboost$final_graph()}} \item \href{#method-AutoCatboost-clone}{\code{AutoCatboost$clone()}} } } @@ -54,7 +55,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
}}\preformatted{AutoCatboost$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
}} +\if{html}{\out{
}}\preformatted{AutoCatboost$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
}} } \subsection{Arguments}{ @@ -72,6 +73,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -113,6 +117,29 @@ Get the internal measure for the auto. } } \if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AutoCatboost-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{AutoCatboost$final_graph(graph, task, pv)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
}} +} +} +\if{html}{\out{
}} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-AutoCatboost-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/AutoExtraTrees.Rd b/man/AutoExtraTrees.Rd index 453930f..d0fa575 100644 --- a/man/AutoExtraTrees.Rd +++ b/man/AutoExtraTrees.Rd @@ -15,6 +15,7 @@ Extra Trees auto. \item \href{#method-AutoExtraTrees-new}{\code{AutoExtraTrees$new()}} \item \href{#method-AutoExtraTrees-graph}{\code{AutoExtraTrees$graph()}} \item \href{#method-AutoExtraTrees-estimate_memory}{\code{AutoExtraTrees$estimate_memory()}} +\item \href{#method-AutoExtraTrees-final_graph}{\code{AutoExtraTrees$final_graph()}} \item \href{#method-AutoExtraTrees-clone}{\code{AutoExtraTrees$clone()}} } } @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
}}\preformatted{AutoExtraTrees$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
}} +\if{html}{\out{
}}\preformatted{AutoExtraTrees$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
}} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -93,6 +97,29 @@ Estimate the memory for the auto. } } \if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AutoExtraTrees-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{AutoExtraTrees$final_graph(graph, task, pv)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
}} +} +} +\if{html}{\out{
}} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-AutoExtraTrees-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/AutoFTTransformer.Rd b/man/AutoFTTransformer.Rd index 89617f7..e8413f5 100644 --- a/man/AutoFTTransformer.Rd +++ b/man/AutoFTTransformer.Rd @@ -19,12 +19,13 @@ FTTransformer auto. } } \if{html}{\out{ -
Inherited methods +
Inherited methods
@@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
}}\preformatted{AutoFTTransformer$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
}} +\if{html}{\out{
}}\preformatted{AutoFTTransformer$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
}} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoFastai.Rd b/man/AutoFastai.Rd index 0ad0f9c..546dc90 100644 --- a/man/AutoFastai.Rd +++ b/man/AutoFastai.Rd @@ -26,6 +26,7 @@ Fastai auto.
  • mlr3automl::Auto$design_default()
  • mlr3automl::Auto$design_set()
  • mlr3automl::Auto$early_stopping_rounds()
    • +
  • mlr3automl::Auto$final_graph()
  • mlr3automl::Auto$search_space()
    • @@ -85,7 +86,7 @@ Default is "cpu".} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoFastai$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoFastai$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -103,6 +104,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoGlmnet.Rd b/man/AutoGlmnet.Rd index f5188f9..ba900e2 100644 --- a/man/AutoGlmnet.Rd +++ b/man/AutoGlmnet.Rd @@ -25,6 +25,7 @@ Glmnet auto.
  • mlr3automl::Auto$design_set()
  • mlr3automl::Auto$early_stopping_rounds()
  • mlr3automl::Auto$estimate_memory()
    • +
  • mlr3automl::Auto$final_graph()
  • mlr3automl::Auto$search_space()
    • @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoGlmnet$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoGlmnet$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoKknn.Rd b/man/AutoKknn.Rd index c0c69ab..a78f2ee 100644 --- a/man/AutoKknn.Rd +++ b/man/AutoKknn.Rd @@ -19,13 +19,14 @@ Kknn auto. } } \if{html}{\out{ -
    Inherited methods +
    Inherited methods
    }} @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoKknn$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoKknn$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoLda.Rd b/man/AutoLda.Rd index 3bf46b5..f394ffe 100644 --- a/man/AutoLda.Rd +++ b/man/AutoLda.Rd @@ -25,6 +25,7 @@ Lda auto.
  • mlr3automl::Auto$design_set()
  • mlr3automl::Auto$early_stopping_rounds()
  • mlr3automl::Auto$estimate_memory()
    • +
  • mlr3automl::Auto$final_graph()
  • mlr3automl::Auto$search_space()
    • @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoLda$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoLda$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -75,6 +76,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoLightgbm.Rd b/man/AutoLightgbm.Rd index 55b31bf..1fa4fa7 100644 --- a/man/AutoLightgbm.Rd +++ b/man/AutoLightgbm.Rd @@ -16,6 +16,7 @@ Lightgbm auto. \item \href{#method-AutoLightgbm-graph}{\code{AutoLightgbm$graph()}} \item \href{#method-AutoLightgbm-estimate_memory}{\code{AutoLightgbm$estimate_memory()}} \item \href{#method-AutoLightgbm-internal_measure}{\code{AutoLightgbm$internal_measure()}} +\item \href{#method-AutoLightgbm-final_graph}{\code{AutoLightgbm$final_graph()}} \item \href{#method-AutoLightgbm-clone}{\code{AutoLightgbm$clone()}} } } @@ -54,7 +55,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoLightgbm$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoLightgbm$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -72,6 +73,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -113,6 +117,29 @@ Get the internal measure for the auto. } } \if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AutoLightgbm-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{AutoLightgbm$final_graph(graph, task, pv)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-AutoLightgbm-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/AutoMlp.Rd b/man/AutoMlp.Rd index ec2db5e..98ff7c5 100644 --- a/man/AutoMlp.Rd +++ b/man/AutoMlp.Rd @@ -19,12 +19,13 @@ Mlp auto. } } \if{html}{\out{ -
    Inherited methods +
    Inherited methods
    @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoMlp$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoMlp$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoRanger.Rd b/man/AutoRanger.Rd index e64aa9b..f017d43 100644 --- a/man/AutoRanger.Rd +++ b/man/AutoRanger.Rd @@ -15,6 +15,7 @@ Ranger auto. \item \href{#method-AutoRanger-new}{\code{AutoRanger$new()}} \item \href{#method-AutoRanger-graph}{\code{AutoRanger$graph()}} \item \href{#method-AutoRanger-estimate_memory}{\code{AutoRanger$estimate_memory()}} +\item \href{#method-AutoRanger-final_graph}{\code{AutoRanger$final_graph()}} \item \href{#method-AutoRanger-clone}{\code{AutoRanger$clone()}} } } @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoRanger$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoRanger$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -93,6 +97,29 @@ Estimate the memory for the auto. } } \if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AutoRanger-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{AutoRanger$final_graph(graph, task, pv)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-AutoRanger-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/AutoResNet.Rd b/man/AutoResNet.Rd index c54bfc2..720d7b7 100644 --- a/man/AutoResNet.Rd +++ b/man/AutoResNet.Rd @@ -19,12 +19,13 @@ ResNet auto. } } \if{html}{\out{ -
    Inherited methods +
    Inherited methods
    @@ -53,7 +54,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoResNet$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoResNet$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -71,6 +72,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoSvm.Rd b/man/AutoSvm.Rd index e2191f9..750dc80 100644 --- a/man/AutoSvm.Rd +++ b/man/AutoSvm.Rd @@ -26,6 +26,7 @@ Svm auto.
  • mlr3automl::Auto$design_set()
  • mlr3automl::Auto$early_stopping_rounds()
  • mlr3automl::Auto$estimate_memory()
    • +
  • mlr3automl::Auto$final_graph()
  • mlr3automl::Auto$search_space()
    • @@ -54,7 +55,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoSvm$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoSvm$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -72,6 +73,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoTabpfn.Rd b/man/AutoTabpfn.Rd index 98f3244..1736600 100644 --- a/man/AutoTabpfn.Rd +++ b/man/AutoTabpfn.Rd @@ -26,6 +26,7 @@ Tabpfn auto.
  • mlr3automl::Auto$design_default()
  • mlr3automl::Auto$design_set()
  • mlr3automl::Auto$early_stopping_rounds()
    • +
  • mlr3automl::Auto$final_graph()
    • }} @@ -84,7 +85,7 @@ Default is "cpu".} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoTabpfn$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoTabpfn$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -102,6 +103,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } diff --git a/man/AutoXgboost.Rd b/man/AutoXgboost.Rd index aa246a1..6a6b65b 100644 --- a/man/AutoXgboost.Rd +++ b/man/AutoXgboost.Rd @@ -16,6 +16,7 @@ Xgboost auto. \item \href{#method-AutoXgboost-graph}{\code{AutoXgboost$graph()}} \item \href{#method-AutoXgboost-estimate_memory}{\code{AutoXgboost$estimate_memory()}} \item \href{#method-AutoXgboost-internal_measure}{\code{AutoXgboost$internal_measure()}} +\item \href{#method-AutoXgboost-final_graph}{\code{AutoXgboost$final_graph()}} \item \href{#method-AutoXgboost-clone}{\code{AutoXgboost$clone()}} } } @@ -54,7 +55,7 @@ Identifier for the new instance.} \subsection{Method \code{graph()}}{ Create the graph for the auto. \subsection{Usage}{ -\if{html}{\out{
    }}\preformatted{AutoXgboost$graph(task, measure, n_threads, timeout, devices)}\if{html}{\out{
    }} +\if{html}{\out{
    }}\preformatted{AutoXgboost$graph(task, measure, n_threads, timeout, devices, pv)}\if{html}{\out{
    }} } \subsection{Arguments}{ @@ -72,6 +73,9 @@ Create the graph for the auto. Devices to use. Allowed values are \code{"cpu"} and \code{"cuda"}. Default is "cpu".} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} } \if{html}{\out{}} } @@ -113,6 +117,29 @@ Get the internal measure for the auto. } } \if{html}{\out{
    }} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AutoXgboost-final_graph}{}}} +\subsection{Method \code{final_graph()}}{ +Modify the graph for the final model. +\subsection{Usage}{ +\if{html}{\out{
    }}\preformatted{AutoXgboost$final_graph(graph, task, pv)}\if{html}{\out{
    }} +} + +\subsection{Arguments}{ +\if{html}{\out{
    }} +\describe{ +\item{\code{graph}}{(\code{mlr3pipelines::GraphLearner})\cr +Graph learner.} + +\item{\code{task}}{(\link[mlr3:Task]{mlr3::Task}).} + +\item{\code{pv}}{(\code{list})\cr +Parameter values.} +} +\if{html}{\out{
    }} +} +} +\if{html}{\out{
    }} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-AutoXgboost-clone}{}}} \subsection{Method \code{clone()}}{ diff --git a/man/mlr3automl-package.Rd b/man/mlr3automl-package.Rd index b6d272c..8f40b68 100644 --- a/man/mlr3automl-package.Rd +++ b/man/mlr3automl-package.Rd @@ -13,17 +13,17 @@ Flexible AutoML system for the 'mlr3' ecosystem. \seealso{ Useful links: \itemize{ - \item \url{https://github.com/mlr-org/mlr3automl} + \item \url{https://github.com/mlr-org/mlr3automl https://mlr3automl.mlr-org.com} \item Report bugs at \url{https://github.com/mlr-org/mlr3automl/issues} } } \author{ -\strong{Maintainer}: Damir Pulatov \email{damirpolat@protonmail.com} +\strong{Maintainer}: Marc Becker \email{marcbecker@posteo.de} (\href{https://orcid.org/0000-0002-8115-0400}{ORCID}) Authors: \itemize{ - \item Marc Becker \email{marcbecker@posteo.de} (\href{https://orcid.org/0000-0002-8115-0400}{ORCID}) + \item Damir Pulatov \email{damirpolat@protonmail.com} \item Baisu Zhou \email{baisu.zhou@outlook.com} } diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml new file mode 100644 index 0000000..652706b --- /dev/null +++ b/pkgdown/_pkgdown.yml @@ -0,0 +1,96 @@ +url: https://mlr3automl.mlr-org.com + +template: + bootstrap: 5 + light-switch: true + math-rendering: mathjax + package: mlr3pkgdowntemplate + +development: + mode: auto + version_label: default + version_tooltip: "Version" + +toc: + depth: 3 + +navbar: + structure: + left: [intro, reference, news, book, articles] + right: [search, github, mattermost, stackoverflow, rss, lightswitch] + components: + home: ~ + reference: + icon: fa fa-file-alt + text: Reference + href: reference/index.html + mattermost: + icon: fa fa-comments + href: https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/ + book: + text: mlr3book + icon: fa fa-link + href: https://mlr3book.mlr-org.com + stackoverflow: + icon: fab fa-stack-overflow + href: https://stackoverflow.com/questions/tagged/mlr3 + rss: + icon: fa-rss + href: https://mlr-org.com/ + +reference: + - title: Classification Learner + contents: + - LearnerClassifAuto + - LearnerClassifAutoCatboost + - LearnerClassifAutoFTTransformer + - LearnerClassifAutoFastai + - LearnerClassifAutoGlmnet + - LearnerClassifAutoKKNN + - LearnerClassifAutoLightGBM + - LearnerClassifAutoMLP + - LearnerClassifAutoRanger + - LearnerClassifAutoResNet + - LearnerClassifAutoSVM + - LearnerClassifAutoTabPFN + - LearnerClassifAutoXgboost + - title: Regression Learner + contents: + - LearnerRegrAuto + - LearnerRegrAutoCatboost + - LearnerRegrAutoExtraTrees + - LearnerRegrAutoFTTransformer + - LearnerRegrAutoFastai + - LearnerRegrAutoGlmnet + - LearnerRegrAutoKKNN + - LearnerRegrAutoLightGBM + - LearnerRegrAutoMLP + - LearnerRegrAutoRanger + - LearnerRegrAutoResNet + - LearnerRegrAutoSVM + - LearnerRegrAutoTabPFN + - LearnerRegrAutoXgboost + - title: Auto + contents: + - Auto + - AutoCatboost + - AutoExtraTrees + - AutoFTTransformer + - AutoFastai + - AutoGlmnet + - AutoKknn + - AutoLda + - AutoLightgbm + - AutoMlp + - AutoRanger + - AutoResNet + - AutoSvm + - AutoTabpfn + - AutoXgboost + - mlr_auto + - title: Callbacks + contents: + - mlr3automl.initial_design_runtime + - title: Package + contents: + - mlr3automl-package diff --git a/pkgdown/favicon/apple-touch-icon.png b/pkgdown/favicon/apple-touch-icon.png new file mode 100644 index 0000000..6231a01 Binary files /dev/null and b/pkgdown/favicon/apple-touch-icon.png differ diff --git a/pkgdown/favicon/favicon-96x96.png b/pkgdown/favicon/favicon-96x96.png new file mode 100644 index 0000000..ef4c666 Binary files /dev/null and b/pkgdown/favicon/favicon-96x96.png differ diff --git a/pkgdown/favicon/favicon.ico b/pkgdown/favicon/favicon.ico new file mode 100644 index 0000000..f51e833 Binary files /dev/null and b/pkgdown/favicon/favicon.ico differ diff --git a/pkgdown/favicon/favicon.svg b/pkgdown/favicon/favicon.svg new file mode 100644 index 0000000..ecc31f2 --- /dev/null +++ b/pkgdown/favicon/favicon.svg @@ -0,0 +1,3 @@ + \ No newline at end of file diff --git a/pkgdown/favicon/site.webmanifest b/pkgdown/favicon/site.webmanifest new file mode 100644 index 0000000..4ebda26 --- /dev/null +++ b/pkgdown/favicon/site.webmanifest @@ -0,0 +1,21 @@ +{ + "name": "", + "short_name": "", + "icons": [ + { + "src": "/web-app-manifest-192x192.png", + "sizes": "192x192", + "type": "image/png", + "purpose": "maskable" + }, + { + "src": "/web-app-manifest-512x512.png", + "sizes": "512x512", + "type": "image/png", + "purpose": "maskable" + } + ], + "theme_color": "#ffffff", + "background_color": "#ffffff", + "display": "standalone" +} \ No newline at end of file diff --git a/pkgdown/favicon/web-app-manifest-192x192.png b/pkgdown/favicon/web-app-manifest-192x192.png new file mode 100644 index 0000000..07fa141 Binary files /dev/null and b/pkgdown/favicon/web-app-manifest-192x192.png differ diff --git a/pkgdown/favicon/web-app-manifest-512x512.png b/pkgdown/favicon/web-app-manifest-512x512.png new file mode 100644 index 0000000..f889a12 Binary files /dev/null and b/pkgdown/favicon/web-app-manifest-512x512.png differ diff --git a/tests/testthat/test_LearnerClassifAuto.R b/tests/testthat/test_LearnerClassifAuto.R index 29aeba9..08e3ed6 100644 --- a/tests/testthat/test_LearnerClassifAuto.R +++ b/tests/testthat/test_LearnerClassifAuto.R @@ -59,6 +59,8 @@ test_that("all learner on cpu work", { expect_class(learner$train(task), "LearnerClassifAuto") expect_set_equal(learner$model$instance$archive$data$branch.selection, c("catboost", "glmnet", "kknn", "lightgbm", "ranger", "svm", "xgboost", "lda", "extra_trees")) + expect_null(learner$model$graph_learner$param_set$values$xgboost.callbacks) + expect_null(learner$model$graph_learner$param_set$values$lightgbm.callbacks) }) test_that("memory limit works", { @@ -123,6 +125,8 @@ test_that("large data set switch works", { rush_plan(n_workers = 2, worker_type = "remote") mirai::daemons(2) + options(bbotk.debug = TRUE) + task = tsk("penguins") learner = lrn("classif.auto", learner_ids = c("catboost", "glmnet", "kknn", "lightgbm", "ranger", "svm", "xgboost", "lda", "extra_trees"), @@ -140,6 +144,16 @@ test_that("large data set switch works", { expect_class(learner$train(task), "LearnerClassifAuto") expect_set_equal(learner$model$instance$archive$data$branch.selection, c("ranger", "xgboost", "catboost", "lightgbm", "extra_trees")) + expect_equal(learner$model$graph_learner$param_set$values$ranger_subsample.frac, 1) + expect_equal(learner$model$graph_learner$param_set$values$xgboost_subsample.frac, 1) + expect_equal(learner$model$graph_learner$param_set$values$catboost_subsample.frac, 1) + expect_equal(learner$model$graph_learner$param_set$values$lightgbm_subsample.frac, 1) + expect_equal(learner$model$graph_learner$param_set$values$extra_trees_subsample.frac, 1) + expect_true(learner$model$graph_learner$param_set$values$ranger_subsample.stratify) + expect_true(learner$model$graph_learner$param_set$values$xgboost_subsample.stratify) + expect_true(learner$model$graph_learner$param_set$values$catboost_subsample.stratify) + expect_true(learner$model$graph_learner$param_set$values$lightgbm_subsample.stratify) + expect_true(learner$model$graph_learner$param_set$values$extra_trees_subsample.stratify) }) test_that("resample works", { diff --git a/vignettes/.gitignore b/vignettes/.gitignore new file mode 100644 index 0000000..9e2bd63 --- /dev/null +++ b/vignettes/.gitignore @@ -0,0 +1,4 @@ +*.html +*.R + +/.quarto/ diff --git a/vignettes/binary.csv b/vignettes/binary.csv new file mode 100644 index 0000000..1fcfc04 --- /dev/null +++ b/vignettes/binary.csv @@ -0,0 +1,22 @@ +task_id,instances,features,n,error_rate,auc_automl,auc_autogluon,auc_autosklearn,auc_ranger,auc_nsrb_catboost,auc_nsrb_xgboost,auc_nsrb_lightgbm,se_autogluon,se_automl,se_autosklearn,se_nsrb_catboost,se_nsrb_lightgbm,se_nsrb_xgboost,se_ranger 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+airlines,539383,8,6490,0,0.730441935427352,0.7301134,0.7273721,0.694990665592163,,,,0.000603091778532364,0.000648809705217837,0.000583604231383636,,,,0.000466112563536697 diff --git a/vignettes/mlr3automl.qmd b/vignettes/mlr3automl.qmd new file mode 100644 index 0000000..22b579d --- /dev/null +++ b/vignettes/mlr3automl.qmd @@ -0,0 +1,217 @@ +--- +title: "mlr3automl" +format: html +--- + +# Introduction + +*mlr3automl* is the Automated Machine Learning (AutoML) package of the [mlr3](https://mlr-org.com/) ecosystem. + + +# Benchmark + +## Binary Classification + +```{r} +#| echo: false +library(gt) +library(data.table) + +tab = fread("/home/marc/repositories/mlr3automl/vignettes/binary.csv") + +gt(tab) %>% + fmt_number( + columns = c("auc_automl", "auc_autogluon", "auc_autosklearn", "auc_ranger", "auc_nsrb_catboost", "auc_nsrb_xgboost", "auc_nsrb_lightgbm"), + decimals = 2 + ) %>% + fmt_percent( + columns = "error_rate", + decimals = 0 + ) %>% + fmt_integer( + columns = c("n", "instances", "features") + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = auc_autogluon, + rows = auc_autogluon > auc_automl & auc_autogluon > auc_autosklearn & auc_autogluon > auc_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = auc_autosklearn, + rows = auc_autosklearn > auc_automl & auc_autosklearn > auc_autogluon & auc_autosklearn > auc_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = auc_automl, + rows = auc_automl > auc_autogluon & auc_automl > auc_autosklearn & auc_automl > auc_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = auc_ranger, + rows = auc_ranger > auc_automl & auc_ranger > auc_autogluon & auc_ranger > auc_autosklearn + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#B069DB") + ), + locations = cells_body( + columns = auc_nsrb_catboost, + rows = auc_nsrb_catboost > auc_automl & auc_nsrb_catboost > auc_autogluon & auc_nsrb_catboost > auc_autosklearn & auc_nsrb_catboost > auc_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#B069DB") + ), + locations = cells_body( + columns = auc_nsrb_xgboost, + rows = auc_nsrb_xgboost > auc_automl & auc_nsrb_xgboost > auc_autogluon & auc_nsrb_xgboost > auc_autosklearn & auc_nsrb_xgboost > auc_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#B069DB") + ), + locations = cells_body( + columns = auc_nsrb_lightgbm, + rows = auc_nsrb_lightgbm > auc_automl & auc_nsrb_lightgbm > auc_autogluon & auc_nsrb_lightgbm > auc_autosklearn & auc_nsrb_lightgbm > auc_ranger + ) + ) %>% + cols_label( + task_id = "Task", + auc_automl = "mlr3automl", + auc_autogluon = "AutoGluon", + auc_autosklearn = "auto-sklearn", + auc_ranger = "ranger", + auc_nsrb_catboost = "nsrb catboost", + auc_nsrb_xgboost = "nsrb xgboost", + auc_nsrb_lightgbm = "nsrb lightgbm", + n = "N Evaluations", + error_rate = "Error Rate", + instances = "Instances", + features = "Features", + ) %>% + cols_hide( + columns = c("se_automl", "se_autogluon", "se_autosklearn", "se_ranger", "se_nsrb_catboost", "se_nsrb_xgboost", "se_nsrb_lightgbm") + ) %>% + tab_spanner( + label = md('**nsrb**'), + columns = c("auc_nsrb_catboost", "auc_nsrb_xgboost", "auc_nsrb_lightgbm") + ) %>% + tab_spanner( + label = md('**automl**'), + columns = c("auc_automl", "auc_autogluon", "auc_autosklearn") + ) %>% + tab_spanner( + label = md('**baseline**'), + columns = c("auc_ranger") + ) +``` + + +## Multiclass Classification + +```{r} +# | echo: false +library(gt) +library(data.table) + +tab = fread("/home/marc/repositories/mlr3automl/vignettes/multiclass.csv") + +gt(tab) %>% + fmt_number( + columns = c("logloss_automl", "logloss_autogluon", "logloss_autosklearn", "logloss_ranger", "logloss_featureless", "logloss_nsrb_catboost", "logloss_nsrb_xgboost", "logloss_nsrb_lightgbm"), + decimals = 2 + ) %>% + fmt_percent( + columns = "error_rate", + decimals = 0 + ) %>% + fmt_integer( + columns = c("n", "instances", "features", "classes") + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = logloss_autogluon, + rows = logloss_autogluon < logloss_automl & logloss_autogluon < logloss_autosklearn & logloss_autogluon < logloss_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = logloss_autosklearn, + rows = logloss_autosklearn < logloss_automl & logloss_autosklearn < logloss_autogluon & logloss_autosklearn < logloss_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = logloss_automl, + rows = logloss_automl < logloss_autogluon & logloss_automl < logloss_autosklearn & logloss_automl < logloss_ranger + ) + ) %>% + tab_style( + style = list( + cell_fill(color = "#90ee90") + ), + locations = cells_body( + columns = logloss_ranger, + rows = logloss_ranger < logloss_automl & logloss_ranger < logloss_autogluon & logloss_ranger < logloss_autosklearn + ) + ) %>% + cols_label( + task_id = "Task", + logloss_automl = "mlr3automl", + logloss_autogluon = "AutoGluon", + logloss_autosklearn = "auto-sklearn", + logloss_ranger = "ranger", + logloss_nsrb_catboost = "nsrb catboost", + logloss_nsrb_xgboost = "nsrb xgboost", + logloss_nsrb_lightgbm = "nsrb lightgbm", + logloss_featureless = "featureless", + n = "N Evaluations", + error_rate = "Error Rate", + instances = "Instances", + features = "Features", + classes = "Classes", + ) %>% + cols_hide( + columns = c("se_automl", "se_autogluon", "se_autosklearn", "se_ranger", "se_featureless", "se_nsrb_catboost", "se_nsrb_xgboost", "se_nsrb_lightgbm") + ) %>% + tab_spanner( + label = md('**nsrb**'), + columns = c("logloss_nsrb_catboost", "logloss_nsrb_xgboost", "logloss_nsrb_lightgbm") + ) %>% + tab_spanner( + label = md('**automl**'), + columns = c("logloss_automl", "logloss_autogluon", "logloss_autosklearn") + ) %>% + tab_spanner( + label = md('**baseline**'), + columns = c("logloss_ranger", "logloss_featureless") + ) +``` diff --git a/vignettes/multiclass.csv b/vignettes/multiclass.csv new file mode 100644 index 0000000..d7290bf --- /dev/null +++ b/vignettes/multiclass.csv @@ -0,0 +1,18 @@ +task_id,instances,features,classes,n,error_rate,logloss_automl,logloss_autogluon,logloss_autosklearn,logloss_ranger,logloss_featureless,logloss_nsrb_catboost,logloss_nsrb_xgboost,logloss_nsrb_lightgbm,se_autogluon,se_automl,se_autosklearn,se_featureless,se_nsrb_catboost,se_nsrb_lightgbm,se_nsrb_xgboost,se_ranger +vehicle,846,19,4,4489,0.00467810202717755,0.246133163650464,0.2975602,0.3287371,0.510561282581669,1.38568463508668,0.417346228374785,0.403397127819529,0.400828178937227,,0.00698817843953814,0.00954073621600206,8.75196107532944e-05,,,,0.0100907914175518 +cnae-9,1080,857,9,1925,0.0592207792207792,0.1978110074977,0.13670169,0.1433449,0.383605591195359,2.19722457733622,0.183215789910806,0.193544966806869,0.136017340635148,,0.0224507384704561,0.0136468275592616,0,,,,0.0103694601320938 +car,1728,7,4,5673,0.00176273576590869,0.00336325567640855,0.00445799303,0.00165220439,0.106281337377552,0.835786293921271,0.000142381808763811,0.00867447124562228,0.00903699561744691,,0.00111708308672078,0.00112451410025991,0.00193086739498989,,,,0.00318904353062951 +mfeat-factors,2000,217,10,4634,0.0336642209753992,0.104556663597505,0.06739112,0.07379011,0.254825952589775,2.30258509299405,0.0764777469290919,0.0868363708318213,0.0750898112199451,,0.0156109055218984,0.00955443793852946,0,,,,0.0068126625016406 +segment,2310,20,7,4471,0.0123014985461865,0.164644724021799,0.05380231,0.06224911,0.185014501231642,1.94591014905531,0.144107199170834,0.156203856960625,0.148784204207072,,0.0124020486003542,0.00818762151706872,0,,,,0.00894840175189936 +fabert,8237,801,7,3137,0,0.779805238351973,0.6823213,0.732713,0.81957240919859,1.87470714450971,0.735900488762994,0.758233912235071,0.736252296217865,,0.0141495553725495,0.00829106589582358,0.000191327211443389,,,,0.00730733440520438 +robert,10000,7201,10,510,0.17843137254902,1.29986025246257,1.265303,1.38254,1.703142824254,2.30224253913693,,1.25048427998283,1.23802438049629,,0.0095081263259262,0.00989761284350929,1.01225183054029e-05,,,,0.00456315597417938 +dilbert,10000,2001,5,1019,0.0716388616290481,0.0212365465041528,0.011531044,0.02948814,0.345697306635468,1.60913038836964,,0.0262178686924159,0.0173229095620056,,0.00379598606715973,0.0024238032368894,6.88809046860954e-06,,,,0.0029826048870314 +jungle_chess_2pcs_raw_endgame_complete,44819,7,3,10897,0.0100945214279159,0.220940363696335,0.006359055,0.202931,0.365947425082544,0.935131176802189,0.225096653055923,0.216816828439813,0.21023144507842,,0.00228145184669591,0.00663809773956365,5.64241219502468e-05,,,,0.00200385029090546 +shuttle,58000,10,7,10191,0.120007850063782,0.000433851922532271,0.0004103703,0.00019398261,0.000999513993301768,0.665633632977827,0.000172939847837588,0.000338603285323662,0.000304703105793594,,0.000105959044951895,6.52572911754825e-05,0.000197431059510338,,,,7.7661666167531e-05 +volkert,58310,181,10,1087,0.0965961361545538,0.798647525057554,0.6736234,0.8331933,0.993226353940388,2.05260271776454,,0.772378708579234,0.722045503644117,,0.00455993559043237,0.0119893109708885,6.62318081584586e-05,,,,0.00275743097891916 +helena,65196,28,100,478,0.50418410041841,2.62423067028888,2.469964,2.48524,2.86122418928546,4.14341318196952,,,,,0.0133154206797103,0.00973240360856452,0.000229507436082131,,,,0.0107391517203801 +connect-4,67557,43,3,3973,0.0072992700729927,0.319769844402902,0.29332,0.3424652,0.455782398418385,0.84456127352411,0.307335718368707,0.304755426273849,0.307800546798303,,0.00238211608853492,0.00396902146014746,2.55615445901264e-05,,,,0.00162967435011445 +Fashion-MNIST,70000,785,10,588,0.185374149659864,0.252519395641236,0.2166764,0.2470057,0.368519094425655,2.30258509299405,,0.235421502589961,,,0.00489295048550023,0.00388432476056722,0,,,,0.00187728299184983 +jannis,83733,55,4,1838,0.0201305767138194,0.673021499200483,0.6470854,0.6723501,0.732399719936977,1.10866842074873,0.666277640906523,0.667610014709809,0.667920427068077,,0.00202470355108686,0.0014239732086275,5.79329889946298e-05,,,,0.00159798786642093 +dionis,416188,61,355,337,0.670623145400593,2.44416591642388,0.2478194,0.5234148,5.85739174873652,5.85739174873652,,,,,0.76552476216906,0.0456489105143936,1.34855287420444e-05,,,,1.34855287420444e-05 +covertype,581012,55,7,536,0.0111940298507463,0.0883230133679485,0.05741523,0.0946388,0.60940715506443,1.20516053044485,,,,,0.00133009751186704,0.00323271539517821,3.58581462169515e-06,,,,0.000486609053327916