private object BuildSummaryAndChart(Product product)
=>
ProductWithData
.Create(product)
.Map(GetEstimate)
.Match(
estimate => PopulateDtoWithEstimate(product, estimate),
error => PopulateDtoWithoutEstimate(product, error.ToString())
);
public static float GetEstimate(ProductWithData product)
{
MLContext mlContext = new MLContext();
IDataView dataView = mlContext.Data.LoadFromEnumerable(product.SalesData);
var estimate =
mlContext.Forecasting.ForecastBySsa(
outputColumnName: nameof(SalesEstimate.ForecastAmount),
inputColumnName: nameof(SalesDatum.Amount),
windowSize: 3,
seriesLength: 24,
trainSize: 24,
horizon: 1)
.Fit(dataView)
.CreateTimeSeriesEngine <SalesDatum, SalesEstimate>(mlContext)
.Predict();
return(estimate.ForecastAmount.First());
}
private static Option <ProductWithData> Convert(this Product product) => ProductWithData.Create(product);
private static float GetEstimate(this ProductWithData product) => SsaEstimator.GetEstimate(product);
private static Either <Error, ProductWithData> ValidProduct(this Product product) => ProductWithData.Create(product);
