## ----------------------------------------------------------------------------- if (!rlang::is_installed(c("gt", "tibble"))) { knitr::knit_exit() } ## ----------------------------------------------------------------------------- library(gt) library(dplyr) tibble::tribble( ~parsnip, ~engine, ~numeric, ~class, ~prob, "`boost_tree()`", "`\"xgboost\"`", "✅", "✅", "✅", "`cubist_rules()`", "`\"Cubist\"`", "✅", "âŒ", "âŒ", "`decision_tree()`", "`\"partykit\"`", "✅", "✅", "✅", "`linear_reg()`", "`\"lm\"`", "✅", "âŒ", "âŒ", "`linear_reg()`", "`\"glmnet\"`", "⚪", "âŒ", "âŒ", "`logistic_reg()`", "`\"glm\"`", "âŒ", "✅", "✅", "`logistic_reg()`", "`\"glmnet\"`", "âŒ", "⚪", "⚪", "`mars()`", "`\"earth\"`", "✅", "⚪", "⚪", "`naive_Bayes()`", "`\"naivebayes\"`", "âŒ", "⚪", "⚪", "`nearest_neighbor()`", "`any`", "âŒ", "âŒ", "âŒ", "`rand_forest()`", "`\"randomForest\"`", "✅", "⚪", "⚪", "`rand_forest()`", "`\"ranger\"`", "✅", "⚪", "⚪" ) |> gt() |> tab_spanner( label = "Model", columns = c(parsnip, engine) ) |> tab_spanner( label = "Regression", columns = c(numeric) ) |> tab_spanner( label = "Classification", columns = c(class, prob) ) |> tab_header( title = "Supported Prediction Types" ) |> cols_align( "center", columns = c(numeric, class, prob) ) |> tab_footnote("✅: Supported") |> tab_footnote("âŒ: Cannot be supported") |> tab_footnote("⚪: Not yet supported") |> fmt_markdown( columns = c(parsnip, engine) ) ## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(orbital) ## ----------------------------------------------------------------------------- all_funs <- ls(getNamespace("orbital")) steps <- grep("orbital.step_", all_funs, value = TRUE) steps <- gsub("orbital.", "", steps) ## ----results='asis'----------------------------------------------------------- cat(paste0("- `", steps, "()`\n"))