revert case

OHDSI · Dec 9, 2024 · 849eeb0 · 849eeb0
1 parent ca20a5c
commit 849eeb0
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Showing 7 changed files with 22 additions and 19 deletions.
diff --git a/R/SklearnClassifierSettings.R b/R/SklearnClassifierSettings.R
@@ -98,7 +98,7 @@ setAdaBoost <- function(nEstimators = list(10, 50, 200),
 }
 
 
-adaBoostClassifierInputs <- function(classifier, param) {
+AdaBoostClassifierInputs <- function(classifier, param) {
   model <- classifier(
     n_estimators = param[[which.max(names(param) == "nEstimators")]],
     learning_rate = param[[which.max(names(param) == "learningRate")]],
@@ -330,7 +330,7 @@ setDecisionTree <- function(criterion = list("gini"),
 }
 
 
-decisionTreeClassifierInputs <- function(classifier, param) {
+DecisionTreeClassifierInputs <- function(classifier, param) {
   model <- classifier(
     criterion = param[[which.max(names(param) == "criterion")]],
     splitter = param[[which.max(names(param) == "splitter")]],
@@ -568,7 +568,7 @@ setNaiveBayes <- function() {
   return(result)
 }
 
-gaussianNBInputs <- function(classifier, param) {
+GaussianNBInputs <- function(classifier, param) {
   model <- classifier()
 
   return(model)
@@ -727,7 +727,7 @@ setRandomForest <- function(ntrees = list(100, 500),
 }
 
 
-randomForestClassifierInputs <- function(classifier, param) {
+RandomForestClassifierInputs <- function(classifier, param) {
   model <- classifier(
     n_estimators = param[[which.max(names(param) == "ntrees")]],
     criterion = param[[which.max(names(param) == "criterion")]],

diff --git a/man/createFeatureEngineeringSettings.Rd b/man/createFeatureEngineeringSettings.Rd
diff --git a/man/setAdaBoost.Rd b/man/setAdaBoost.Rd
diff --git a/man/setDecisionTree.Rd b/man/setDecisionTree.Rd
diff --git a/man/setRandomForest.Rd b/man/setRandomForest.Rd
diff --git a/man/setSVM.Rd b/man/setSVM.Rd
diff --git a/tests/testthat/test-sklearnClassifierSettings.R b/tests/testthat/test-sklearnClassifierSettings.R
@@ -20,7 +20,7 @@ test_that("setAdaBoost settings work checks", {
   expect_equal(attr(adset$param, "settings")$pythonClass, "AdaBoostClassifier")
 
 
-  inputs <- adaBoostClassifierInputs(list, adset$param[[1]])
+  inputs <- AdaBoostClassifierInputs(list, adset$param[[1]])
   expect_equal(
     names(inputs),
     c("n_estimators", "learning_rate", "algorithm", "random_state")
@@ -101,7 +101,7 @@ test_that("setNaiveBayes settings work checks", {
   expect_equal(attr(nbset$param, "settings")$pythonModule, "sklearn.naive_bayes")
   expect_equal(attr(nbset$param, "settings")$pythonClass, "GaussianNB")
 
-  inputs <- gaussianNBInputs(list, nbset$param[[1]])
+  inputs <- GaussianNBInputs(list, nbset$param[[1]])
   expect_equal(names(inputs), NULL)
 })
 
@@ -137,7 +137,7 @@ test_that("setRandomForest settings work checks", {
   expect_equal(attr(rfset$param, "settings")$pythonModule, "sklearn.ensemble")
   expect_equal(attr(rfset$param, "settings")$pythonClass, "RandomForestClassifier")
 
-  inputs <- randomForestClassifierInputs(list, rfset$param[[1]])
+  inputs <- RandomForestClassifierInputs(list, rfset$param[[1]])
   expect_equal(
     names(inputs),
     c(