Error While Evaluating model : 'Could not find feature column 'Features' (Parameter 'inputSchema')'

Question

I am working on to create recommendation system in C# using FFM (Field-aware Factorization Machines), where my data set have 4 feature column of string type, and Label column if int type. The dataset and code is as following:

DataSet

 public  IDataView  LoadData(MLContext mlContext)
        {
            var partnerhubDataPath = Path.Combine("C://ABB Work//Projects//CustomerPortal-Sitecore10//Sitecore.PartnerHub//MLNetApp", "DataSet", "DummySet.csv");

            var data = File.ReadAllLines(partnerhubDataPath).Select(x => new PartnerhubPredictionData()
            {
                ProjectTool = x[1].ToString(),
                DiscoverTag = x[2].ToString(),
                UserEmailId = x[0].ToString(),
                VideoName = x[4].ToString(),
                ViIndexTag = x[3].ToString(),
                Label = x[6] != 0? true: false
            }) ;
            IDataView trainingDataView = mlContext.Data.LoadFromEnumerable(data);
                //mlContext.Data.LoadFromTextFile<PartnerhubPredictionData>(partnerhubDataPath, 
                  //                          hasHeader: true, separatorChar: ',');

            var debug = trainingDataView.Preview();

            return (trainingDataView);
        }

        public  ITransformer BuildAndTrainModel(MLContext mlContext, IDataView trainingDataView)
        {
            var option = new FieldAwareFactorizationMachineTrainer.Options
            {
                LabelColumnName = "Label",  
                FeatureColumnName = "Features",  
                Shuffle = false
            };

            IEstimator<ITransformer> estimator = mlContext.Transforms.Categorical.OneHotEncoding("UserEmailIdOneHot", "UserEmailId").
                Append(mlContext.Transforms.Categorical.OneHotEncoding("ProjectToolOneHot", "ProjectTool")).
                Append(mlContext.Transforms.Categorical.OneHotEncoding("DiscoverTagOneHot", "DiscoverTag")).
                Append(mlContext.Transforms.Categorical.OneHotEncoding("ViIndexTagOneHot", "ViIndexTag")).
                Append(mlContext.Transforms.Concatenate("Features",new string[]{ "UserEmailIdOneHot", "ProjectToolOneHot", "DiscoverTagOneHot",
                 "ViIndexTagOneHot" })).
                Append(mlContext.BinaryClassification.Trainers.FieldAwareFactorizationMachine(option));
            
            var model = estimator.Fit(trainingDataView);  
            return model;

        }

         void EvaluateModel(MLContext mlContext, IDataView trainingData, ITransformer model)
        {
            Console.WriteLine("=============== Evaluating the model ===============");

            var testingData = mlContext.Data.ShuffleRows(trainingData);
            testingData = mlContext.Data.TakeRows(testingData, 8);
            var scoredData = model.Transform(testingData);
            
            IEstimator<ITransformer> sdcaEstimator =  mlContext.Regression.Trainers.Sdca();
            var cvResults = mlContext.Regression.CrossValidate(trainingData, sdcaEstimator, labelColumnName: "Label", numberOfFolds: 5);
            IEnumerable<double> rSquared = cvResults.OrderByDescending(fold => fold.Metrics.RSquared).
                Select(fold => fold.Metrics.RSquared).ToArray();
            IEnumerable<double> rootMeanSquareSquared = cvResults.Select(fold => fold.Metrics.RootMeanSquaredError);
            Console.WriteLine("RSquared : " +   rSquared.ToString());
            Console.WriteLine(" Root Mean Squared Error: " + rootMeanSquareSquared.ToString());
        }

As I don't have test dataset , I am trying cross validation here, but I am constantly getting error while evaluating the model. Even though the sdcaEstimator have the Features Column

ErrorMessage

I want to know where I the code is going wrong, since I have done everything following this blog.