Scores to Label mapping

src/Microsoft.ML.Core/Data/ITransformModel.cs

@@ -25,6 +25,10 @@ public interface ITransformModel
         /// </summary>
         ISchema InputSchema { get; }
 
+        /// <summary>
+        /// Schema of the transform model.
+        /// </summary>
+        IDataView Schema { get; }
         /// <summary>
         /// Apply the transform(s) in the model to the given input data.
         /// </summary>

src/Microsoft.ML.Data/EntryPoints/TransformModel.cs

@@ -44,6 +44,14 @@ public ISchema InputSchema
             get { return _schemaRoot; }
         }
 
+        /// <summary>
+        /// Schema of the transform model.
+        /// </summary>
+        public IDataView Schema
+        {
+            get { return _chain; }
+        }
+
         /// <summary>
         /// Create a TransformModel containing the transforms from "result" back to "input".
         /// </summary>

src/Microsoft.ML/PredictionModel.cs

@@ -29,6 +29,33 @@ internal Runtime.EntryPoints.TransformModel PredictorModel
             get { return _predictorModel; }
         }
 
+        /// <summary>
+        /// Returns labels that correspond to indices of the score array in the case of 
+        /// multi-class classification problem.
+        /// </summary>
+        /// <param name="mapping">Label to score mapping</param>
+        /// <param name="scoreColumnName">Name of the score column</param>
+        /// <returns></returns>
+        public bool TryGetScoreLabelMapping(out string[] mapping, string scoreColumnName = "Score")
+        {
+            mapping = null;
+            IDataView idv = _predictorModel.Schema;
+            int colIndex = -1;
+            if (!idv.Schema.TryGetColumnIndex(scoreColumnName, out colIndex))
+                return false;
+
+            VBuffer<DvText> labels = default(VBuffer<DvText>);
+            idv.Schema.GetMetadata(MetadataUtils.Kinds.SlotNames, colIndex, ref labels);
+
+            Contracts.Assert(labels.IsDense);
+
+            mapping = new string[labels.Count];
+            for (int index = 0; index < labels.Count; index++)
+                mapping[index] = labels.Values[index].ToString();
+
+            return true;
+        }
+
         /// <summary>
         /// Read model from file asynchronously.
         /// </summary>

test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationWithStringLabelTests.cs

@@ -30,6 +30,14 @@ public void TrainAndPredictIrisModelWithStringLabelTest()
             pipeline.Add(new StochasticDualCoordinateAscentClassifier());
 
             PredictionModel<IrisDataWithStringLabel, IrisPrediction> model = pipeline.Train<IrisDataWithStringLabel, IrisPrediction>();
+            string[] scoreLabels;
+            model.TryGetScoreLabelMapping(out scoreLabels);
+
+            Assert.NotNull(scoreLabels);
+            Assert.Equal(3, scoreLabels.Length);
+            Assert.True(scoreLabels[0] == "Iris-setosa");
+            Assert.True(scoreLabels[1] == "Iris-versicolor");
+            Assert.True(scoreLabels[2] == "Iris-virginica");
 
             IrisPrediction prediction = model.Predict(new IrisDataWithStringLabel()
             {