Merge pull request #3 from dotnet/master

Update fork
zeahmed · May 10, 2018 · 3fb99ae · 3fb99ae
2 parents bd83d91 + e9cd4bc
commit 3fb99ae
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Showing 3 changed files with 16 additions and 16 deletions.
diff --git a/DotnetCLIVersion.txt b/DotnetCLIVersion.txt
@@ -1 +1 @@
-2.1.2
+2.1.200
diff --git a/build/publish.proj b/build/publish.proj
@@ -3,7 +3,7 @@
 
   <PropertyGroup>
     <PublishSymbolsPackage>Microsoft.SymbolUploader.Build.Task</PublishSymbolsPackage>
-    <EnablePublishSymbols>false</EnablePublishSymbols>
+    <EnablePublishSymbols Condition="'$(EnablePublishSymbols)'==''" >true</EnablePublishSymbols>
   </PropertyGroup>
 
   <Import Project="$(PackagesDir)\$(PublishSymbolsPackage.ToLower())\$(PublishSymbolsPackageVersion)\build\PublishSymbols.targets" />

diff --git a/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs b/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs
@@ -32,8 +32,8 @@ public void TrainAndPredictSentimentModelTest()
                 OutputTokens = true,
                 StopWordsRemover = new PredefinedStopWordsRemover(),
                 VectorNormalizer = TextTransformTextNormKind.L2,
-                CharFeatureExtractor = new NGramNgramExtractor() { NgramLength = 2, AllLengths = true },
-                WordFeatureExtractor = new NGramNgramExtractor() { NgramLength = 3, AllLengths = false }
+                CharFeatureExtractor = new NGramNgramExtractor() { NgramLength = 3, AllLengths = false },
+                WordFeatureExtractor = new NGramNgramExtractor() { NgramLength = 2, AllLengths = true }
             });
 
             pipeline.Add(new FastTreeBinaryClassifier() { NumLeaves = 5, NumTrees = 5, MinDocumentsInLeafs = 2 });
@@ -65,16 +65,16 @@ public void TrainAndPredictSentimentModelTest()
             var evaluator = new BinaryClassificationEvaluator();
             BinaryClassificationMetrics metrics = evaluator.Evaluate(model, testData);
 
-            Assert.Equal(.7222, metrics.Accuracy, 4);
-            Assert.Equal(.9643, metrics.Auc, 1);
-            Assert.Equal(.96, metrics.Auprc, 2);
+            Assert.Equal(.5556, metrics.Accuracy, 4);
+            Assert.Equal(.8, metrics.Auc, 1);
+            Assert.Equal(.87, metrics.Auprc, 2);
             Assert.Equal(1, metrics.Entropy, 3);
-            Assert.Equal(.7826, metrics.F1Score, 4);
-            Assert.Equal(.812, metrics.LogLoss, 3);
-            Assert.Equal(18.831, metrics.LogLossReduction, 3);
+            Assert.Equal(.6923, metrics.F1Score, 4);
+            Assert.Equal(.969, metrics.LogLoss, 3);
+            Assert.Equal(3.083, metrics.LogLossReduction, 3);
             Assert.Equal(1, metrics.NegativePrecision, 3);
-            Assert.Equal(.444, metrics.NegativeRecall, 3);
-            Assert.Equal(.643, metrics.PositivePrecision, 3);
+            Assert.Equal(.111, metrics.NegativeRecall, 3);
+            Assert.Equal(.529, metrics.PositivePrecision, 3);
             Assert.Equal(1, metrics.PositiveRecall);
 
             ConfusionMatrix matrix = metrics.ConfusionMatrix;
@@ -88,10 +88,10 @@ public void TrainAndPredictSentimentModelTest()
             Assert.Equal(0, matrix[0, 1]);
             Assert.Equal(0, matrix["positive", "negative"]);
 
-            Assert.Equal(5, matrix[1, 0]);
-            Assert.Equal(5, matrix["negative", "positive"]);
-            Assert.Equal(4, matrix[1, 1]);
-            Assert.Equal(4, matrix["negative", "negative"]);
+            Assert.Equal(8, matrix[1, 0]);
+            Assert.Equal(8, matrix["negative", "positive"]);
+            Assert.Equal(1, matrix[1, 1]);
+            Assert.Equal(1, matrix["negative", "negative"]);
         }
 
         public class SentimentData