build_readme

DESCRIPTION

@@ -1,60 +1,68 @@
 Package: tabnet
 Title: Fit 'TabNet' Models for Classification and Regression
-Version: 0.6.0
+Version: 0.5.0
 Authors@R: c(
-    person(given = "Daniel", family = "Falbel", role = c("aut"), email = "[email protected]"),
-    person(family = "RStudio", role = c("cph")),
-    person(given = "Christophe", family = "Regouby", role = c("cre", "ctb"), email = "[email protected]"),
-    person(given = "Egill", family = "Fridgeirsson", role = c("ctb")),
-    person(given = "Philipp", family = "Haarmeyer", role = c("ctb")),
-    person(given = "Sven", family = "Verweij", role = c("ctb"),  comment = c(ORCID = "0000-0002-5573-3952"))
-    )
-Description: Implements the 'TabNet' model by Sercan O. Arik et al. (2019) <arXiv:1908.07442> 
-    with 'Coherent Hierarchical Multi-label Classification Networks' by Giunchiglia et al.
-    <arXiv:2010.10151> and provides a consistent interface for fitting and creating 
-    predictions. It's also fully compatible with the 'tidymodels' ecosystem.
+    person("Daniel", "Falbel", , "[email protected]", role = "aut"),
+    person(, "RStudio", role = "cph"),
+    person("Christophe", "Regouby", , "[email protected]", role = c("cre", "ctb")),
+    person("Egill", "Fridgeirsson", role = "ctb"),
+    person("Philipp", "Haarmeyer", role = "ctb"),
+    person("Sven", "Verweij", role = "ctb",
+           comment = c(ORCID = "0000-0002-5573-3952"))
+  )
+Description: Implements the 'TabNet' model by Sercan O. Arik et al. (2019)
+    <arXiv:1908.07442> with 'Coherent Hierarchical Multi-label
+    Classification Networks' by Giunchiglia et al.  <arXiv:2010.10151> and
+    provides a consistent interface for fitting and creating predictions.
+    It's also fully compatible with the 'tidymodels' ecosystem.
 License: MIT + file LICENSE
-Encoding: UTF-8
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
 URL: https://mlverse.github.io/tabnet/, https://github.com/mlverse/tabnet
 BugReports: https://github.com/mlverse/tabnet/issues
 Depends:
     R (>= 3.6)
 Imports: 
-    torch (>= 0.4.0),
+    coro,
+    data.tree,
+    dials,
+    dplyr,
+    ggplot2,
     hardhat (>= 1.3.0),
     magrittr,
+    Matrix,
+    methods,
+    parsnip,
     progress,
+    purrr,
     rlang,
-    methods,
-    dplyr,
+    stats,
+    stringr,
     tibble,
     tidyr,
-    coro,
+    torch (>= 0.4.0),
+    tune,
+    utils,
     vctrs,
+    vip,
+    withr,
     zeallot
 Suggests: 
-    testthat (>= 3.0.0),
-    data.tree,
-    Matrix,
+    knitr,
     modeldata,
+    patchwork,
     recipes,
-    rsample,
-    parsnip,
-    dials,
-    withr,
-    knitr,
     rmarkdown,
-    vip,
+    rsample,
+    testthat (>= 3.0.0),
+    tidymodels,
     tidyverse,
-    ggplot2,
-    purrr,
-    stringr,
-    tune,
+    visdat,
     workflows,
     yardstick
-VignetteBuilder: knitr
+VignetteBuilder: 
+    knitr
 Config/testthat/edition: 3
 Config/testthat/parallel: false
 Config/testthat/start-first: interface, explain, params
+Encoding: UTF-8
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.1

README.md

@@ -98,13 +98,16 @@ cbind(test, predict(fit, test)) %>%
 #> 1 accuracy  binary         0.837
 #> 2 precision binary         0.837
 #> 3 recall    binary         1
+```
+
+``` r
 
 cbind(test, predict(fit, test, type = "prob")) %>% 
   roc_auc(Attrition, .pred_No)
 #> # A tibble: 1 × 3
 #>   .metric .estimator .estimate
 #>   <chr>   <chr>          <dbl>
-#> 1 roc_auc binary         0.548
+#> 1 roc_auc binary         0.546
 ```
 
 ## Explain model on test-set with attention map