Add loadable attribute for LinearMulticlassModelParameters (#3217)

Author: Ivanidzo4ka

src/Microsoft.ML.StandardTrainers/Standard/LogisticRegression/MulticlassLogisticRegression.cs

@@ -31,6 +31,10 @@
     "Multiclass LR Executor",
     MaximumEntropyModelParameters.LoaderSignature)]
 
+[assembly: LoadableClass(typeof(LinearMulticlassModelParameters), null, typeof(SignatureLoadModel),
+    "Multiclass LR No Calib",
+    LinearMulticlassModelParameters.LoaderSignature)]
+
 [assembly: LoadableClass(typeof(void), typeof(LbfgsMaximumEntropyMulticlassTrainer), null, typeof(SignatureEntryPointModule), LbfgsMaximumEntropyMulticlassTrainer.LoadNameValue)]
 
 namespace Microsoft.ML.Trainers

test/Microsoft.ML.Tests/TrainerEstimators/SdcaTests.cs

@@ -19,7 +19,6 @@ public void SdcaWorkout()
 
             var data = TextLoaderStatic.CreateLoader(Env, ctx => (Label: ctx.LoadFloat(0), Features: ctx.LoadFloat(1, 10)))
                 .Load(dataPath).Cache();
-
             var binaryData = ML.Transforms.Conversion.ConvertType("Label", outputKind: DataKind.Boolean)
                 .Fit(data.AsDynamic).Transform(data.AsDynamic);
 
@@ -36,11 +35,15 @@ public void SdcaWorkout()
 
             TestEstimatorCore(regressionTrainer, data.AsDynamic);
             var mcData = ML.Transforms.Conversion.MapValueToKey("Label").Fit(data.AsDynamic).Transform(data.AsDynamic);
-
+            
             var mcTrainer = ML.MulticlassClassification.Trainers.SdcaMaximumEntropy(
                 new SdcaMaximumEntropyMulticlassTrainer.Options { ConvergenceTolerance = 1e-2f, MaximumNumberOfIterations = 10 });
             TestEstimatorCore(mcTrainer, mcData);
 
+            var mcTrainerNonCalibrated = ML.MulticlassClassification.Trainers.SdcaNonCalibrated(
+                new SdcaNonCalibratedMulticlassTrainer.Options { ConvergenceTolerance = 1e-2f, MaximumNumberOfIterations = 10 });
+            TestEstimatorCore(mcTrainerNonCalibrated, mcData);
+
             Done();
         }