Removed nameof for explicit strings

Author: prathyusha12345

samples/csharp/getting-started/Regression_TaxiFarePrediction/TaxiFarePrediction/TaxiFarePredictionConsoleApp/Program.cs

@@ -29,10 +29,6 @@ internal static class Program
 
         private static string ModelPath = GetAbsolutePath(ModelRelativePath);
 
-        private static string VendorIdEncoded = nameof(VendorIdEncoded);
-        private static string RateCodeEncoded = nameof(RateCodeEncoded);
-        private static string PaymentTypeEncoded = nameof(PaymentTypeEncoded);
-
         static void Main(string[] args) //If args[0] == "svg" a vector-based chart will be created instead a .png chart
         {
             //Create ML Context with seed for repeteable/deterministic results
@@ -64,13 +60,13 @@ private static ITransformer BuildTrainEvaluateAndSaveModel(MLContext mlContext)
 
             // STEP 2: Common data process configuration with pipeline data transformations
             var dataProcessPipeline = mlContext.Transforms.CopyColumns(outputColumnName: DefaultColumnNames.Label, inputColumnName: nameof(TaxiTrip.FareAmount))
-                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: VendorIdEncoded, inputColumnName: nameof(TaxiTrip.VendorId)))
-                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: RateCodeEncoded, inputColumnName: nameof(TaxiTrip.RateCode)))
-                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: PaymentTypeEncoded,inputColumnName: nameof(TaxiTrip.PaymentType)))
+                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "VendorIdEncoded", inputColumnName: nameof(TaxiTrip.VendorId)))
+                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "RateCodeEncoded", inputColumnName: nameof(TaxiTrip.RateCode)))
+                            .Append(mlContext.Transforms.Categorical.OneHotEncoding(outputColumnName: "PaymentTypeEncoded",inputColumnName: nameof(TaxiTrip.PaymentType)))
                             .Append(mlContext.Transforms.Normalize(outputColumnName: nameof(TaxiTrip.PassengerCount), mode: NormalizerMode.MeanVariance))
                             .Append(mlContext.Transforms.Normalize(outputColumnName: nameof(TaxiTrip.TripTime), mode: NormalizerMode.MeanVariance))
                             .Append(mlContext.Transforms.Normalize(outputColumnName: nameof(TaxiTrip.TripDistance), mode: NormalizerMode.MeanVariance))
-                            .Append(mlContext.Transforms.Concatenate(DefaultColumnNames.Features, VendorIdEncoded, RateCodeEncoded, PaymentTypeEncoded, nameof(TaxiTrip.PassengerCount)
+                            .Append(mlContext.Transforms.Concatenate(DefaultColumnNames.Features, "VendorIdEncoded", "RateCodeEncoded", "PaymentTypeEncoded", nameof(TaxiTrip.PassengerCount)
                             , nameof(TaxiTrip.TripTime), nameof(TaxiTrip.TripDistance)));
 
             // (OPTIONAL) Peek data (such as 5 records) in training DataView after applying the ProcessPipeline's transformations into "Features"