block5.fs

// set up a learning pipeline
let pipeline = 
    EstimatorChain()

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

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

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

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

// train the model
let model = partitions.TrainSet |> pipeline.Fit

// the rest of the code goes here...