public List <TaxiFarePrediction> RunMultiplePredictions(int numberOfPredictions)
{
// Load data as input for predictions.
IDataView inputDataForPredictions = context.Data.LoadFromTextFile <TaxiTrip>(_datasetFile, hasHeader: true, separatorChar: ',');
Console.WriteLine("Predictions from saved model:");
Console.WriteLine($"\n \n Test {numberOfPredictions} transactions, from the test datasource, that should be predicted as fraud (true):");
var transactionList = new List <TaxiFarePrediction>();
TaxiTripFarePredictionWithContribution prediction;
TaxiFarePrediction explainedPrediction;
context.Data.CreateEnumerable <TaxiTrip>(inputDataForPredictions, reuseRowObject: false)
.Take(numberOfPredictions)
.Select(testData => testData)
.ToList()
.ForEach(testData =>
{
testData.PrintToConsole();
prediction = predictionEngine.Predict(testData);
explainedPrediction = new TaxiFarePrediction(prediction.FareAmount, prediction.GetFeatureContributions(model.GetOutputSchema(inputDataForPredictions.Schema)));
transactionList.Add(explainedPrediction);
});
return(transactionList);
}
static void Main(string[] args)
{
// Create single instance of sample data from first line of dataset for model input
TaxiFareInput sampleData = CreateSingleDataSample(DATA_FILEPATH);
// Make a single prediction on the sample data and print results
TaxiFarePrediction predictionResult = ConsumeModel.Predict(sampleData);
Console.WriteLine("Using model to make single prediction -- Comparing actual Fare_amount with predicted Fare_amount from sample data...\n\n");
Console.WriteLine($"vendor_id: {sampleData.Vendor_id}");
Console.WriteLine($"rate_code: {sampleData.Rate_code}");
Console.WriteLine($"passenger_count: {sampleData.Passenger_count}");
Console.WriteLine($"trip_time_in_secs: {sampleData.Trip_time_in_secs}");
Console.WriteLine($"trip_distance: {sampleData.Trip_distance}");
Console.WriteLine($"payment_type: {sampleData.Payment_type}");
Console.WriteLine($"\n\nActual Fare_amount: {sampleData.Fare_amount} \nPredicted Fare_amount: {predictionResult.Score}\n\n");
Console.WriteLine("=============== End of process, hit any key to finish ===============");
Console.ReadKey();
}
// Change this code to create your own sample data
#region CreateSingleDataSample
// Method to load single row of dataset to try a single prediction
private static TaxiFarePrediction CreateSingleDataSample(string dataFilePath)
{
// Create MLContext
MLContext mlContext = new MLContext();
// Load dataset
IDataView dataView = mlContext.Data.LoadFromTextFile <TaxiFarePrediction>(
path: dataFilePath,
hasHeader: true,
separatorChar: ',',
allowQuoting: true,
allowSparse: false);
// Use first line of dataset as model input
// You can replace this with new test data (hardcoded or from end-user application)
TaxiFarePrediction sampleForPrediction = mlContext.Data.CreateEnumerable <TaxiFarePrediction>(dataView, false)
.First();
return(sampleForPrediction);
}