diff --git a/Project.toml b/Project.toml
index 08cea0d..2f2a9cc 100644
--- a/Project.toml
+++ b/Project.toml
@@ -24,7 +24,7 @@ Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MLBase = "f0e99cf1-93fa-52ec-9ecc-5026115318e0"
-MLDataUtils = "cc2ba9b6-d476-5e6d-8eaf-a92d5412d41d"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 NumericalTypeAliases = "be9b823e-291e-41a1-b8ce-806204e78f92"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 PlotThemes = "ccf2f8ad-2431-5c83-bf29-c5338b663b6a"
@@ -61,7 +61,6 @@ JLD2 = "0.4"
 JSON = "0.21"
 Latexify = "0.16"
 MLBase = "0.9"
-MLDataUtils = "0.5"
 NumericalTypeAliases = "0.1, 0.2"
 PlotThemes = "3"
 Plots = "1"
diff --git a/src/DCCR.jl b/src/DCCR.jl
index 473c8f2..5a05758 100644
--- a/src/DCCR.jl
+++ b/src/DCCR.jl
@@ -42,7 +42,7 @@ using
     # Latexify,               # latexify
     Logging,                # Printing diagnostics
     MLBase,                 # confusmat
-    MLDataUtils,            # stratifiedobs
+    MLUtils,                # splitobs
     NumericalTypeAliases,   # RealMatrix, IntegerVector, etc.
     Plots,                  # Plotting
     Printf,                 # Formatted number printing
diff --git a/src/lib/c3/functions.jl b/src/lib/c3/functions.jl
index ac947eb..ad5079c 100644
--- a/src/lib/c3/functions.jl
+++ b/src/lib/c3/functions.jl
@@ -473,14 +473,14 @@ function get_n_categories(ddvfa::DDVFA, n_classes::Int)
 end
 
 """
-Wrapper of `stratifiedobs`, returns a manual train/test x/y split from a data matrix and labels using MLDataUtils.
+Wrapper of `splitobs`, returns a manual train/test x/y split from a data matrix and labels using MLDataUtils.
 
 # Arguments
 - `data::RealMatrix`: the feature data to split into training and testing.
 - `targets::IntegerVector`: the labels corresponding to the data to split into training and testing.
 """
 function get_manual_split(data::RealMatrix, targets::IntegerVector)
-    (X_train, y_train), (X_test, y_test) = stratifiedobs((data, targets))
+    (X_train, y_train), (X_test, y_test) = splitobs((data, targets))
     return (X_train, y_train), (X_test, y_test)
 end