more tibble naming fxes

Author: topepo

R/logistic_reg_data.R

@@ -333,8 +333,8 @@ set_pred(
   value = list(
     pre = NULL,
     post = function(x, object) {
-      x <- as_tibble(x)
       colnames(x) <- object$lvl
+      x <- as_tibble(x)
       x
     },
     func = c(pkg = "keras", fun = "predict_proba"),

R/predict.R

@@ -184,7 +184,7 @@ format_num <- function(x) {
     return(x)
 
   if (isTRUE(ncol(x) > 1)) {
-    x <- as_tibble(x)
+    x <- as_tibble(x, .name_repair = "minimal")
     names(x) <- paste0(".pred_", names(x))
   } else {
     x <- tibble(.pred = x)
@@ -201,8 +201,8 @@ format_class <- function(x) {
 }
 
 format_classprobs <- function(x) {
-  x <- as_tibble(x)
   names(x) <- paste0(".pred_", names(x))
+  x <- as_tibble(x)
   x
 }
 

tests/testthat/test_multinom_reg_keras.R

@@ -155,7 +155,7 @@ test_that('classification probabilities', {
 
   keras_pred <-
     keras::predict_proba(lr_fit$fit, as.matrix(te_dat[, -5])) %>%
-    as_tibble() %>%
+    as_tibble(.name_repair = "minimal") %>%
     setNames(paste0(".pred_", lr_fit$lvl))
 
   parsnip_pred <- predict(lr_fit, te_dat[, -5], type = "prob")
@@ -172,7 +172,7 @@ test_that('classification probabilities', {
 
   keras_pred <-
     keras::predict_proba(plrfit$fit, as.matrix(te_dat[, -5])) %>%
-    as_tibble() %>%
+    as_tibble(.name_repair = "minimal") %>%
     setNames(paste0(".pred_", lr_fit$lvl))
   parsnip_pred <- predict(plrfit, te_dat[, -5], type = "prob")
   expect_equal(as.data.frame(keras_pred), as.data.frame(parsnip_pred))