public IActionResult YearAnalysis(RegressionModelInput input)
{
// Load the model
MLContext mlContext = new MLContext();
ITransformer mlModel = mlContext.Model.Load(_hostingEnvironment.ContentRootPath + FileHelper.RegressionModelPath, out var modelInputSchema);
var predictionEngine = mlContext.Model.CreatePredictionEngine <RegressionModelInput, RegressionModelOutput>(mlModel);
//Input
// Try model on sample data
// Predict a whole year, starting with startDate
DateTime startDate = new DateTime(2019, 1, 1);
var predictedValues = new List <(string date, float calls)>();
var calls = GetCalls();
for (DateTime date = startDate; date < startDate.AddYears(1); date = date.AddDays(1))
{
var dateString = date.ToString("MM'/'dd'/'yyyy 00:00:00");
var row = calls.Where(x => x.Date == date);
string weatherConditions = row.FirstOrDefault().WeatherConditions;
float callCount = 0;
for (int i = 0; i < 24; i++)
{
var prediction = predictionEngine.Predict(new RegressionModelInput()
{
Hour = (float)i,
Month = (float)date.Month,
DayOfWeek = date.DayOfWeek.ToString(),
WeatherConditions = weatherConditions
});
callCount += prediction.Score;
}
predictedValues.Add((dateString, callCount));
}
return(Json(new
{
Status = 1,
result = predictedValues
}));
}
public IActionResult Analysis(RegressionModelInput input)
{
// Load the model
MLContext mlContext = new MLContext();
ITransformer mlModel = mlContext.Model.Load(_hostingEnvironment.ContentRootPath + FileHelper.RegressionModelPath, out var modelInputSchema);
var predictionEngine = mlContext.Model.CreatePredictionEngine <RegressionModelInput, RegressionModelOutput>(mlModel);
var inputdate = DateTime.Parse(input.DayOfWeek);
//Input
// Try model on sample data
// Predict values for each hour of this day
var calls = GetCalls();
var actual = calls.Where(x => x.Date == new DateTime(2019, inputdate.Month, inputdate.Day)).Select(x => new ChartOutput()
{
x = Convert.ToInt32(x.Hour), y = x.Calls
});
var predictedValues = new List <ChartOutput>();
for (int i = 0; i < 24; i++)
{
var prediction = predictionEngine.Predict(new RegressionModelInput()
{
Hour = (float)i,
Month = inputdate.Month,
DayOfWeek = inputdate.DayOfWeek.ToString(),
WeatherConditions = input.WeatherConditions
});
predictedValues.Add(new ChartOutput {
x = i, y = Math.Round(prediction.Score)
});
}
return(Json(new
{
Status = 1,
actual = actual.ToArray(),
predicted = predictedValues.ToArray()
}));
}