private static void TestSinglePrediction(LocalEnvironment mlcontext, ITransformer model)
{
//Prediction test
// Create prediction engine and make prediction.
var engine = model.MakePredictionFunction <TaxiTrip, TaxiTripFarePrediction>(mlcontext);
//Sample:
//vendor_id,rate_code,passenger_count,trip_time_in_secs,trip_distance,payment_type,fare_amount
//VTS,1,1,1140,3.75,CRD,15.5
var taxiTripSample = new TaxiTrip()
{
VendorId = "VTS",
RateCode = "1",
PassengerCount = 1,
TripTime = 1140,
TripDistance = 3.75f,
PaymentType = "CRD",
FareAmount = 0 // To predict. Actual/Observed = 15.5
};
var prediction = engine.Predict(taxiTripSample);
Console.WriteLine($"**********************************************************************");
Console.WriteLine($"Predicted fare: {prediction.FareAmount:0.####}, actual fare: 29.5");
Console.WriteLine($"**********************************************************************");
}
private static void TestSinglePrediction(MLContext mlContext)
{
//Sample:
//vendor_id,rate_code,passenger_count,trip_time_in_secs,trip_distance,payment_type,fare_amount
//VTS,1,1,1140,3.75,CRD,15.5
var taxiTripSample = new TaxiTrip()
{
VendorId = "VTS",
RateCode = "1",
PassengerCount = 1,
TripTime = 1140,
TripDistance = 3.75f,
PaymentType = "CRD",
FareAmount = 0 // To predict. Actual/Observed = 15.5
};
///
ITransformer trainedModel = mlContext.Model.Load(ModelPath, out var modelInputSchema);
// Create prediction engine related to the loaded trained model
var predEngine = mlContext.Model.CreatePredictionEngine <TaxiTrip, TaxiTripFarePrediction>(trainedModel);
//Score
var resultprediction = predEngine.Predict(taxiTripSample);
///
Console.WriteLine($"**********************************************************************");
Console.WriteLine($"Predicted fare: {resultprediction.FareAmount:0.####}, actual fare: 15.5");
Console.WriteLine($"**********************************************************************");
}
private static void TestSinglePrediction(MLContext mlContext)
{
//Sample:
//vendor_id,rate_code,passenger_count,trip_time_in_secs,trip_distance,payment_type,fare_amount
//VTS,1,1,1140,3.75,CRD,15.5
var taxiTripSample = new TaxiTrip()
{
VendorId = "VTS",
RateCode = "1",
PassengerCount = 1,
TripTime = 1140,
TripDistance = 3.75f,
PaymentType = "CRD",
FareAmount = 0 // To predict. Actual/Observed = 15.5
};
///
ITransformer trainedModel;
using (var stream = new FileStream(ModelPath, FileMode.Open, FileAccess.Read, FileShare.Read))
{
trainedModel = mlContext.Model.Load(stream);
}
// Create prediction engine related to the loaded trained model
var predFunction = trainedModel.MakePredictionFunction<TaxiTrip, TaxiTripFarePrediction>(mlContext);
//Score
var resultprediction = predFunction.Predict(taxiTripSample);
///
Console.WriteLine($"**********************************************************************");
Console.WriteLine($"Predicted fare: {resultprediction.FareAmount:0.####}, actual fare: 15.5");
Console.WriteLine($"**********************************************************************");
}
private static void TestSinglePrediction(MLContext mlContext)
{
//Sample:
//vendor_id,rate_code,passenger_count,trip_time_in_secs,trip_distance,payment_type,fare_amount
//VTS,1,1,1140,3.75,CRD,15.5
var taxiTripSample = new TaxiTrip()
{
VendorId = "VTS",
RateCode = "1",
PassengerCount = 1,
TripTime = 1140,
TripDistance = 3.75f,
PaymentType = "CRD",
FareAmount = 0 // To predict. Actual/Observed = 15.5
};
var modelScorer = new Common.ModelScorer <TaxiTrip, TaxiTripFarePrediction>(mlContext);
modelScorer.LoadModelFromZipFile(ModelPath);
var resultprediction = modelScorer.PredictSingle(taxiTripSample);
Console.WriteLine($"**********************************************************************");
Console.WriteLine($"Predicted fare: {resultprediction.FareAmount:0.####}, actual fare: 15.5");
Console.WriteLine($"**********************************************************************");
}
private static void LoadInitialDataInCache(string initialData)
{
var currentLine = string.Empty;
string datapath = ConfigurationManager.AppSettings["BaseDataRelativePath"];
if (String.IsNullOrEmpty(datapath))
{
Console.WriteLine("Data path cannot be null or empty.");
return;
}
string filepath = GetAbsolutePath($"{datapath}/taxi-fare-initial.csv");
IDistributedList <TaxiTrip> initialDataList = Cache.DataTypeManager.GetList <TaxiTrip>(initialData);
if (initialDataList == null)
{
initialDataList = Cache.DataTypeManager.CreateList <TaxiTrip>(initialData);
using (StreamReader r = new StreamReader(filepath))
{
while ((currentLine = r.ReadLine()) != null)
{
string[] incomingData = currentLine.Split(",");
TaxiTrip data = new TaxiTrip();
data.RateCode = float.Parse(incomingData[0]);
data.PassengerCount = float.Parse(incomingData[1]);
data.TripTime = float.Parse(incomingData[2]);
data.TripDistance = float.Parse(incomingData[3]);
data.FareAmount = float.Parse(incomingData[4]);
initialDataList.Add(data);
TrainingData.Add(data);
}
}
}
}