diff --git a/src/SharpLearning.Benchmarks/Benchmarks.ClassificationModels.cs b/src/SharpLearning.Benchmarks/Benchmarks.ClassificationModels.cs
deleted file mode 100644
index 91b8960a..00000000
--- a/src/SharpLearning.Benchmarks/Benchmarks.ClassificationModels.cs
+++ /dev/null
@@ -1,45 +0,0 @@
-using BenchmarkDotNet.Attributes;
-using SharpLearning.Containers.Matrices;
-using SharpLearning.DecisionTrees.Learners;
-using SharpLearning.DecisionTrees.Models;
-
-namespace SharpLearning.Benchmarks;
-
-public static partial class Benchmarks
-{
-    [MemoryDiagnoser]
-    public class ClassificationModels
-    {
-        const int Rows = 1000;
-        const int Cols = 10;
-        const int MinTargetValue = 0;
-        const int MaxTargetValue = 10;
-        F64Matrix m_features;
-        double[] m_targets;
-
-        // Define learners here. Use default parameters for benchmarks.
-        readonly ClassificationDecisionTreeLearner m_classificationDecisionTreeLearner = new();
-        ClassificationDecisionTreeModel m_classificationDecisionTreeModel;
-        //readonly ClassificationAdaBoostLearner m_classificationAdaBoostLearner = new();
-        //readonly ClassificationRandomForestLearner m_classificationRandomForestLearner = new();
-        //readonly ClassificationExtremelyRandomizedTreesLearner m_classificationExtremelyRandomizedTreesLearner = new();
-        //readonly ClassificationBinomialGradientBoostLearner m_classificationBinomialGradientBoostLearner = new();
-
-        [GlobalSetup]
-        public void GlobalSetup()
-        {
-            var seed = 42;
-            m_targets = DataGenerator.GenerateIntegers(Rows, cols: 1,
-                MinTargetValue, MaxTargetValue, seed);
-            var features = DataGenerator.GenerateDoubles(Rows, Cols, seed);
-            m_features = new F64Matrix(features, Rows, Cols);
-            m_classificationDecisionTreeModel = m_classificationDecisionTreeLearner.Learn(m_features, m_targets);
-        }
-
-        [Benchmark]
-        public void ClassificationDecisionTreeModel_Predict()
-        {
-            m_classificationDecisionTreeModel.Predict(m_features);
-        }
-    }
-}
diff --git a/src/SharpLearning.Benchmarks/program.cs b/src/SharpLearning.Benchmarks/program.cs
index 25391271..60eeefae 100644
--- a/src/SharpLearning.Benchmarks/program.cs
+++ b/src/SharpLearning.Benchmarks/program.cs
@@ -16,6 +16,5 @@
 var config = (Debugger.IsAttached ? new DebugInProcessConfig() : DefaultConfig.Instance)
     .WithSummaryStyle(SummaryStyle.Default.WithMaxParameterColumnWidth(200));
 
-BenchmarkRunner.Run(typeof(Benchmarks.ClassificationModels), config, args);
-//BenchmarkRunner.Run(typeof(Benchmarks.ClassificationLearners), config, args);
-//BenchmarkRunner.Run(typeof(Benchmarks.RegressionLearners), config, args);
+BenchmarkRunner.Run(typeof(Benchmarks.ClassificationLearners), config, args);
+BenchmarkRunner.Run(typeof(Benchmarks.RegressionLearners), config, args);