ML.NET static API loading traing DataSet NOT from a file

mlnet-static-api-not-using-dataset-file.cs

var dataReader = TextLoader.CreateReader(env,
                c => (
                    CustomerId: c.LoadText(0),
                    ProductId: c.LoadText(1),
                    Quantity: c.LoadFloat(2),
                    Label: c.LoadBool(3)),
                    separator: ',', hasHeader: true);
 
FieldAwareFactorizationMachinePredictor pred = null;
var ctx = new BinaryClassificationContext(env);
 
var est = dataReader.MakeNewEstimator()
    .Append(row => (CustomerId_OHE: row.CustomerId.OneHotEncoding(), ProductId_OHE: row.ProductId.OneHotEncoding(), row.Label))
    .Append(row => (Features: row.CustomerId_OHE.ConcatWith(row.ProductId_OHE), row.Label))
    .Append(row => (row.Label,
    preds: ctx.Trainers.FieldAwareFactorizationMachine(
        row.Label,
        new[] { row.Features },
        advancedSettings: ffmArguments => ffmArguments.Shuffle = false,
        onFit: p => pred = p)));
 
// NO NEED FOR THIS SINCE I’M NOT READING FROM A FILE
//var dataSource = reader.Read(new MultiFileSource(orderItemsLocation));
 
// Load data in IDataView from a Database
IEnumerable<Orders> myData = GetDataFromDatabase();
var trainData = env.CreateStreamingDataView(myData);
 
var model = est.Fit(trainData);