Remove intercept coming from workflows based on engine encodings (#1033)

* for intercepts coming from workflows (details in the PR description)

* bump version for extratests

* update NEWS

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.1.1.9003
+Version: 1.1.1.9004
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "[email protected]", role = "aut"),

NEWS.md

@@ -10,6 +10,9 @@
 
 * When computing censoring weights, the resulting vectors are no longer named (#1023).
 
+* Fixed a bug in the integration with workflows where using a model formula with a formula preprocessor could result in a double intercept (#1033).
+
+
 # parsnip 1.1.1
 
 * Fixed bug where prediction on rank deficient `lm()` models produced `.pred_res` instead of `.pred`. (#985)

R/convert_data.R

@@ -45,6 +45,10 @@
     rlang::abort("`composition` should be either 'data.frame' or 'matrix'.")
   }
 
+  if (remove_intercept) {
+    data <- data[, colnames(data) != "(Intercept)", drop = FALSE]
+  }
+
   ## Assemble model.frame call from call arguments
   mf_call <- quote(model.frame(formula, data))
   mf_call$na.action <- match.call()$na.action # TODO this should work better

R/fit_helpers.R

@@ -6,6 +6,15 @@
 form_form <-
   function(object, control, env, ...) {
 
+    encoding_info <-
+      get_encoding(class(object)[1]) %>%
+      dplyr::filter(mode == object$mode, engine == object$engine)
+
+    remove_intercept <- encoding_info %>% dplyr::pull(remove_intercept)
+    if (remove_intercept) {
+      env$data <- env$data[, colnames(env$data) != "(Intercept)", drop = FALSE]
+    }
+
     if (inherits(env$data, "data.frame")) {
       check_outcome(eval_tidy(rlang::f_lhs(env$formula), env$data), object)
     }