fix remaining test failures

Some more manual data entry and # classes in outcome variable issues.

Author: simonpcouch

tests/testthat/test_boost_tree_xgboost.R

@@ -65,7 +65,7 @@ test_that('xgboost classification prediction', {
   )
 
   xy_pred <- predict(xy_fit$fit, newdata = xgb.DMatrix(data = as.matrix(hpc[1:8, num_pred])), type = "class")
-  xy_pred <- matrix(xy_pred, ncol = 3, byrow = TRUE)
+  xy_pred <- matrix(xy_pred, ncol = 4, byrow = TRUE)
   xy_pred <- factor(levels(hpc$class)[apply(xy_pred, 1, which.max)], levels = levels(hpc$class))
   expect_equal(xy_pred, predict(xy_fit, new_data = hpc[1:8, num_pred], type = "class")$.pred_class)
 
@@ -77,7 +77,7 @@ test_that('xgboost classification prediction', {
   )
 
   form_pred <- predict(form_fit$fit, newdata = xgb.DMatrix(data = as.matrix(hpc[1:8, num_pred])), type = "class")
-  form_pred <- matrix(form_pred, ncol = 3, byrow = TRUE)
+  form_pred <- matrix(form_pred, ncol = 4, byrow = TRUE)
   form_pred <- factor(levels(hpc$class)[apply(form_pred, 1, which.max)], levels = levels(hpc$class))
   expect_equal(form_pred, predict(form_fit, new_data = hpc[1:8, num_pred], type = "class")$.pred_class)
 })

tests/testthat/test_mars.R

@@ -188,17 +188,21 @@ test_that('mars execution', {
 test_that('mars prediction', {
   skip_if_not_installed("earth")
 
-  uni_pred <- c(5.02371514510488, 4.70502120747471, 4.78973285129011, 4.81152592623742,
-                5.08745393263092)
-  inl_pred <- c(5.07584328502019, 4.64927636051174, 4.82786784324037, 4.74001260567429,
-                5.15379794835255)
+  uni_pred <- c(30.1466666666667, 30.1466666666667, 30.1466666666667,
+                30.1466666666667, 30.1466666666667)
+  inl_pred <- c(538.268789262046, 141.024903718634, 141.024903718634,
+                141.024903718634, 141.024903718634)
   mv_pred <-
     structure(
-      list(Sepal.Width =
-             c(3.4874092243636, 3.34173526636919, 3.17647644756747, 3.14280919018489, 3.41457224536639),
-           Petal.Width =
-             c(0.237414046784062, 0.221455118452782, 0.18348960240454, 0.219523313672823, 0.229434582618422
-             )), class = "data.frame", row.names = c(NA, -5L))
+      list(compounds =
+             c(371.334864384913, 129.475162245595, 256.094366313268,
+               129.475162245595, 129.475162245595),
+           input_fields =
+             c(430.476046435458, 158.833790342308, 218.07635084308,
+               158.833790342308, 158.833790342308)
+           ),
+      class = "data.frame", row.names = c(NA, -5L)
+    )
 
   res_xy <- fit_xy(
     hpc_basic,

tests/testthat/test_predict_formats.R

@@ -13,7 +13,7 @@ context("check predict output structures")
 lm_fit <-
   linear_reg(mode = "regression") %>%
   set_engine("lm") %>%
-  fit(class ~ ., data = hpc)
+  fit(compounds ~ ., data = hpc)
 
 class_dat <- airquality[complete.cases(airquality),]
 class_dat$Ozone <- factor(ifelse(class_dat$Ozone >= 31, "high", "low"))

tests/testthat/test_rand_forest_ranger.R

@@ -310,11 +310,11 @@ test_that('additional descriptor tests', {
 
   ##
 
-  exp_wts <- quo(c(min(.lvls()), 20, 10))
+  exp_wts <- quo(c(min(.lvls()), 20, 10, 1))
 
   descr_other_xy <- fit_xy(
     rand_forest(mode = "classification", mtry = 2) %>%
-      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10)),
+      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10, 1)),
     x = hpc[, 1:4],
     y = hpc$class,
     control = ctrl
@@ -324,7 +324,7 @@ test_that('additional descriptor tests', {
 
   descr_other_f <- fit(
     rand_forest(mode = "classification", mtry = 2) %>%
-      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10)),
+      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10, 1)),
     class ~ ., data = hpc,
     control = ctrl
   )
@@ -333,7 +333,7 @@ test_that('additional descriptor tests', {
 
   descr_other_xy <- fit_xy(
     rand_forest(mode = "classification", mtry = 2) %>%
-      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10)),
+      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10, 1)),
     x = hpc[, 1:4],
     y = hpc$class,
     control = ctrl
@@ -343,7 +343,7 @@ test_that('additional descriptor tests', {
 
   descr_other_f <- fit(
     rand_forest(mode = "classification", mtry = 2) %>%
-      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10)),
+      set_engine("ranger", class.weights = c(min(.lvls()), 20, 10, 1)),
     class ~ ., data = hpc,
     control = ctrl
   )