public IActionResult GetProductUnitDemandEstimation(string productId,
[FromQuery] int year, [FromQuery] int month,
[FromQuery] float units, [FromQuery] float avg,
[FromQuery] int count, [FromQuery] float max,
[FromQuery] float min, [FromQuery] float prev)
{
// Build product sample
var inputExample = new ProductData(productId, year, month, units, avg, count, max, min, prev);
ProductUnitPrediction nextMonthUnitDemandEstimation = null;
//Set the critical section if using Singleton for the PredictionFunction object
//
//lock(this.productSalesPredFunction)
//{
// Returns prediction
nextMonthUnitDemandEstimation = this.productSalesPredFunction.Predict(inputExample);
//}
//
// Note that if using Scoped instead of singleton in DI/IoC you can remove the critical section
// It depends if you want better performance in single Http calls (using singleton)
// versus better scalability ann global performance if you have many Http requests/threads
// since the critical section is a bottleneck reducing the execution to one thread for that particular Predict() mathod call
//
return(Ok(nextMonthUnitDemandEstimation.Score));
}
public IActionResult GetProductUnitDemandEstimation(string productId,
[FromQuery] int year, [FromQuery] int month,
[FromQuery] float units, [FromQuery] float avg,
[FromQuery] int count, [FromQuery] float max,
[FromQuery] float min, [FromQuery] float prev)
{
// Build product sample
var inputExample = new ProductData(productId, year, month, units, avg, count, max, min, prev);
ProductUnitPrediction nextMonthUnitDemandEstimation = null;
//Predict
nextMonthUnitDemandEstimation = this.productSalesModel.Predict(inputExample);
return(Ok(nextMonthUnitDemandEstimation.Score));
}
/// <summary>
/// Predict samples using saved model
/// </summary>
/// <param name="outputModelPath">Model file path</param>
/// <returns></returns>
public static async Task TestPrediction(string outputModelPath = "product_month_fastTreeTweedie.zip")
{
Console.WriteLine("*********************************");
Console.WriteLine("Testing product forecasting model");
// Read the model that has been previously saved by the method SaveModel
var model = await PredictionModel.ReadAsync <ProductData, ProductUnitPrediction>(outputModelPath);
// Build sample data
ProductData dataSample = new ProductData()
{
ProductId = "428",
Year = 2018,
Month = 8,
Units = 404,
Avg = 5.179487f,
Count = 78,
Max = 60,
Min = 1,
Prev = 335
};
// Predict sample data
ProductUnitPrediction prediction = model.Predict(dataSample);
Console.WriteLine($"Product: {dataSample.ProductId}, month: {dataSample.Month + 1}, year: {dataSample.Year} - Real value: {dataSample.Units}, Forecasting: {prediction.Score}");
dataSample = new ProductData()
{
ProductId = "428",
Year = 2018,
Month = 9,
Units = 302,
Avg = 5.206896f,
Count = 58,
Max = 40,
Min = 1,
Prev = 404
};
prediction = model.Predict(dataSample);
Console.WriteLine($"Product: {dataSample.ProductId}, month: {dataSample.Month + 1}, year: {dataSample.Year} - Forecasting: {prediction.Score}");
}
