Clean FastTree.cs and FastTreeArguments.cs following instructions in #2613

Author: wschin

docs/samples/Microsoft.ML.Samples/Dynamic/FastTreeRegression.cs

@@ -35,16 +35,6 @@ public static void Example()
 
             // Get the trained model parameters.
             var modelParams = model.LastTransformer.Model;
-
-            // Let's see where an example with Parity = 1 and Induced = 1 would end up in the single trained tree.
-            var testRow = new VBuffer<float>(2, new[] { 1.0f, 1.0f });
-            // Use the path object to pass to GetLeaf, which will populate path with the IDs of th nodes from root to leaf.
-            List<int> path = default;
-            // Get the ID of the leaf this example ends up in tree 0.
-            var leafID = modelParams.GetLeaf(0, in testRow, ref path);
-            // Get the leaf value for this leaf ID in tree 0.
-            var leafValue = modelParams.GetLeafValue(0, leafID);
-            Console.WriteLine("The leaf value in tree 0 is: " + leafValue);
         }
     }
 }

src/Microsoft.ML.FastTree/BoostingFastTree.cs

@@ -29,7 +29,7 @@ private protected BoostingFastTreeTrainerBase(IHostEnvironment env,
             double learningRate)
             : base(env, label, featureColumn, weightColumn, groupIdColumn, numLeaves, numTrees, minDatapointsInLeaves)
         {
-            FastTreeTrainerOptions.LearningRates = learningRate;
+            FastTreeTrainerOptions.LearningRate = learningRate;
         }
 
         private protected override void CheckOptions(IChannel ch)
@@ -42,10 +42,10 @@ private protected override void CheckOptions(IChannel ch)
             if (FastTreeTrainerOptions.CompressEnsemble && FastTreeTrainerOptions.WriteLastEnsemble)
                 throw ch.Except("Ensemble compression cannot be done when forcing to write last ensemble (hl)");
 
-            if (FastTreeTrainerOptions.NumLeaves > 2 && FastTreeTrainerOptions.HistogramPoolSize > FastTreeTrainerOptions.NumLeaves - 1)
+            if (FastTreeTrainerOptions.NumberOfLeaves > 2 && FastTreeTrainerOptions.HistogramPoolSize > FastTreeTrainerOptions.NumberOfLeaves - 1)
                 throw ch.Except("Histogram pool size (ps) must be at least 2.");
 
-            if (FastTreeTrainerOptions.NumLeaves > 2 && FastTreeTrainerOptions.HistogramPoolSize > FastTreeTrainerOptions.NumLeaves - 1)
+            if (FastTreeTrainerOptions.NumberOfLeaves > 2 && FastTreeTrainerOptions.HistogramPoolSize > FastTreeTrainerOptions.NumberOfLeaves - 1)
                 throw ch.Except("Histogram pool size (ps) must be at most numLeaves - 1.");
 
             if (FastTreeTrainerOptions.EnablePruning && !HasValidSet)
@@ -63,12 +63,12 @@ private protected override void CheckOptions(IChannel ch)
         private protected override TreeLearner ConstructTreeLearner(IChannel ch)
         {
             return new LeastSquaresRegressionTreeLearner(
-                TrainSet, FastTreeTrainerOptions.NumLeaves, FastTreeTrainerOptions.MinDocumentsInLeafs, FastTreeTrainerOptions.EntropyCoefficient,
+                TrainSet, FastTreeTrainerOptions.NumberOfLeaves, FastTreeTrainerOptions.MinExampleCountPerLeaf, FastTreeTrainerOptions.EntropyCoefficient,
                 FastTreeTrainerOptions.FeatureFirstUsePenalty, FastTreeTrainerOptions.FeatureReusePenalty, FastTreeTrainerOptions.SoftmaxTemperature,
-                FastTreeTrainerOptions.HistogramPoolSize, FastTreeTrainerOptions.RngSeed, FastTreeTrainerOptions.SplitFraction, FastTreeTrainerOptions.FilterZeroLambdas,
+                FastTreeTrainerOptions.HistogramPoolSize, FastTreeTrainerOptions.RandomSeed, FastTreeTrainerOptions.FeatureFractionPerSplit, FastTreeTrainerOptions.FilterZeroLambdas,
                 FastTreeTrainerOptions.AllowEmptyTrees, FastTreeTrainerOptions.GainConfidenceLevel, FastTreeTrainerOptions.MaxCategoricalGroupsPerNode,
                 FastTreeTrainerOptions.MaxCategoricalSplitPoints, BsrMaxTreeOutput(), ParallelTraining,
-                FastTreeTrainerOptions.MinDocsPercentageForCategoricalSplit, FastTreeTrainerOptions.Bundling, FastTreeTrainerOptions.MinDocsForCategoricalSplit, FastTreeTrainerOptions.Bias);
+                FastTreeTrainerOptions.MinExamplePercentageForCategoricalSplit, FastTreeTrainerOptions.Bundling, FastTreeTrainerOptions.MinExamplesForCategoricalSplit, FastTreeTrainerOptions.Bias);
         }
 
         private protected override OptimizationAlgorithm ConstructOptimizationAlgorithm(IChannel ch)
@@ -96,7 +96,7 @@ private protected override OptimizationAlgorithm ConstructOptimizationAlgorithm(
             optimizationAlgorithm.ObjectiveFunction = ConstructObjFunc(ch);
             optimizationAlgorithm.Smoothing = FastTreeTrainerOptions.Smoothing;
             optimizationAlgorithm.DropoutRate = FastTreeTrainerOptions.DropoutRate;
-            optimizationAlgorithm.DropoutRng = new Random(FastTreeTrainerOptions.RngSeed);
+            optimizationAlgorithm.DropoutRng = new Random(FastTreeTrainerOptions.RandomSeed);
             optimizationAlgorithm.PreScoreUpdateEvent += PrintTestGraph;
 
             return optimizationAlgorithm;