This code is part of the ML.NET taxi fare demo

mlnet-taxidemo-createmodel.cs

// set up a learning pipeline
var pipeline = mlContext.Transforms.CopyColumns(
    inputColumnName:"FareAmount", 
    outputColumnName:"Label")

    // one-hot encode all text features
    .Append(mlContext.Transforms.Categorical.OneHotEncoding("VendorId"))
    .Append(mlContext.Transforms.Categorical.OneHotEncoding("RateCode"))
    .Append(mlContext.Transforms.Categorical.OneHotEncoding("PaymentType"))

    // combine all input features into a single column 
    .Append(mlContext.Transforms.Concatenate(
        "Features", 
        "VendorId", 
        "RateCode", 
        "PassengerCount", 
        "TripDistance", 
        "PaymentType"))

    // cache the data to speed up training
    .AppendCacheCheckpoint(mlContext)

    // use the fast tree learner 
    .Append(mlContext.Regression.Trainers.FastTree());

// train the model
Console.Write("Training the model....");
var model = pipeline.Fit(partitions.TrainSet);
Console.WriteLine("done");