inst/doc/tidymodels-interface.R

In tabnet: Fit 'TabNet' Models for Classification and Regression

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)

## ----setup--------------------------------------------------------------------
# library(tabnet)
# library(tidymodels)
# library(modeldata)

## -----------------------------------------------------------------------------
# set.seed(123)
# data("lending_club", package = "modeldata")
# split <- initial_split(lending_club, strata = Class)
# train <- training(split)
# test  <- testing(split)

## -----------------------------------------------------------------------------
# rec <- recipe(Class ~ ., train) %>%
#   step_normalize(all_numeric())

## -----------------------------------------------------------------------------
# mod <- tabnet(epochs = 50, batch_size = 128) %>%
#   set_engine("torch", verbose = TRUE) %>%
#   set_mode("classification")

## -----------------------------------------------------------------------------
# wf <- workflow() %>%
#   add_model(mod) %>%
#   add_recipe(rec)

## -----------------------------------------------------------------------------
# folds <- vfold_cv(train, v = 5)

## -----------------------------------------------------------------------------
# fit_rs <- wf %>%
#   fit_resamples(folds)

## -----------------------------------------------------------------------------
# collect_metrics(fit_rs)

## -----------------------------------------------------------------------------
# model <- wf %>% fit(train)
# test %>%
#   bind_cols(
#     predict(model, test, type = "prob")
#   ) %>%
#   roc_auc(Class, .pred_bad)