rebuild

zachmayer · Jul 26, 2024 · b6709a2 · b6709a2
1 parent aa0cf3c
commit b6709a2
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Showing 8 changed files with 11,960 additions and 40 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -45,7 +45,6 @@ Imports:
     methods,
     pbapply,
     ggplot2,
-    digest,
     lattice,
     gridExtra,
     data.table,

diff --git a/R/caretEnsemble.R b/R/caretEnsemble.R
@@ -176,7 +176,7 @@ varImp.caretEnsemble <- function(object, ...) {
 
   # Order and return
   data.table::setorderv(imp, "overall", order = -1L)
-  data.table::setcolorder(imp, c("var", "overallq", model_names))
+  data.table::setcolorder(imp, c("var", "overall", model_names))
   imp
 }
 

diff --git a/cobertura.xml b/cobertura.xml
diff --git a/coverage-report.html b/coverage-report.html
diff --git a/coverage.rds b/coverage.rds
diff --git a/man/varImp.caretEnsemble.Rd b/man/varImp.caretEnsemble.Rd
diff --git a/man/varImpDataTable.Rd b/man/varImpDataTable.Rd
diff --git a/tests/testthat/test-ensembleMethods.R b/tests/testthat/test-ensembleMethods.R
@@ -16,24 +16,19 @@ data(Y.class)
 test_that("We can get variable importance in ensembles", {
   set.seed(2239L)
   ens.class <- caretEnsemble(models.class, trControl = trainControl(method = "none"))
-  # varImp struggles with the rf in our test suite, why?
-  models.subset <- models.reg[2L:4L]
-  class(models.subset) <- "caretList"
-  ens.reg <- caretEnsemble(models.subset, trControl = trainControl(method = "none"))
+  ens.reg <- caretEnsemble(models.reg, trControl = trainControl(method = "none"))
   expect_is(varImp(ens.class), "data.frame")
-  expect_is(varImp(ens.class, weight = TRUE), "data.frame")
-  expect_is(varImp(ens.class, scale = TRUE, weight = TRUE), "data.frame")
+  expect_is(varImp(ens.class, scale = TRUE), "data.frame")
   expect_is(varImp(ens.reg), "data.frame")
-  expect_is(varImp(ens.reg, weight = TRUE), "data.frame")
-  expect_is(varImp(ens.reg, scale = TRUE, weight = TRUE), "data.frame")
+  expect_is(varImp(ens.reg, scale = TRUE), "data.frame")
 })
 
 test_that("varImp works for caretEnsembles", {
   set.seed(2239L)
   for (models in list(models.class, models.reg)) {
     ens <- caretEnsemble(models, trControl = trainControl(method = "none"))
-    expected_names <- c("overall", names(ens$models))
-    expected_row_names <- c(
+    expected_names <- c("var", "overall", names(ens$models))
+    expected_var_names <- c(
       "Intercept",
       "Speciesversicolor",
       "Speciesvirginica",
@@ -42,39 +37,22 @@ test_that("varImp works for caretEnsembles", {
       "Petal.Length"
     )
     for (s in c(TRUE, FALSE)) {
-      for (w in c(TRUE, FALSE)) {
-        i <- varImp(ens, scale = s, weight = w)
-        expect_is(i, "data.frame")
-        expect_named(i, expected_names)
-        expect_equal(sort(row.names(i)), sort(expected_row_names))
-      }
+      i <- varImp(ens, scale = s)
+      expect_is(i, "data.frame")
+      expect_named(i, expected_names)
+      expect_equal(sort(i[["var"]]), sort(expected_var_names))
     }
   }
 })
 
 test_that("We get the right dimensions back", {
-  ncol1 <- 5L
-  ncol2 <- 4L
-  nrow1 <- 6L
-  nrow2 <- 6L
   set.seed(2239L)
   ens.class <- caretEnsemble(models.class, trControl = trainControl(method = "none"))
-  # varImp struggles with the rf in our test suite, why?
-  models.subset <- models.reg[2L:4L]
-  class(models.subset) <- "caretList"
-  ens.reg <- caretEnsemble(models.subset, trControl = trainControl(method = "none"))
-  expect_equal(ncol(varImp(ens.class)), ncol1)
-  expect_equal(ncol(varImp(ens.class, weight = FALSE)), ncol1)
-  expect_equal(ncol(varImp(ens.class, weight = TRUE)), ncol1)
-  expect_equal(ncol(varImp(ens.reg)), ncol2)
-  expect_equal(ncol(varImp(ens.reg, weight = FALSE)), ncol2)
-  expect_equal(ncol(varImp(ens.reg, weight = TRUE)), ncol2)
-  expect_equal(nrow(varImp(ens.class)), nrow1)
-  expect_equal(nrow(varImp(ens.class, weight = FALSE)), nrow1)
-  expect_equal(nrow(varImp(ens.class, weight = TRUE)), nrow1)
-  expect_equal(nrow(varImp(ens.reg)), nrow2)
-  expect_equal(nrow(varImp(ens.reg, weight = FALSE)), nrow2)
-  expect_equal(nrow(varImp(ens.reg, weight = TRUE)), nrow2)
+  ens.reg <- caretEnsemble(models.reg, trControl = trainControl(method = "none"))
+  expect_equal(ncol(varImp(ens.class)), 6L)
+  expect_equal(ncol(varImp(ens.reg)), 6L)
+  expect_equal(nrow(varImp(ens.class)), 6L)
+  expect_equal(nrow(varImp(ens.reg)), 6L)
 })
 
 context("Do metric extraction functions work as expected")