public bool Train([FromBody] List <Rfm> data)
{
if (data != null && data.Any())
{
var segmentator = new CustomersSegmentator();
segmentator.Train(data);
return(true);
}
return(false);
}
public List <int> PredictList([FromBody] List <ClusteringData> data)
{
var segmentator = new CustomersSegmentator();
return(segmentator.Predict(data));
}
public async Task <IActionResult> OnPost(IFormFile file, string train, string predict, string download)
{
// var fileName = file.FileName;
using (var stream = new MemoryStream())
{
file.CopyTo(stream);
var customers = new ExcelImportProcessor().GetImportData(stream);
var rfmCalculateService = new RfmCalculateService();
var calculatedScores = rfmCalculateService.CalculateRfmScores(customers);
var segmentator = new CustomersSegmentator(_hostingEnvironment.ContentRootPath);
if (!string.IsNullOrEmpty(train))
{
var businessData = calculatedScores.Select(x => new Rfm
{
R = x.R,
F = x.F,
M = x.M
}).ToList();
_clusteringMetrics = segmentator.Train(businessData);
ViewData["ClusteringMetrics"] = _clusteringMetrics.AvgMinScore.ToString();
}
else if (!string.IsNullOrEmpty(predict))
{
var businessData = calculatedScores.Select(x => new ClusteringData
{
R = x.R,
F = x.F,
M = x.M
}).ToList();
var predictions = segmentator.Predict(businessData);
var predictedCustomers = calculatedScores.Select((t, i) => new PredictionResult
{
CustomerId = t.CustomerId.ToString(), R = t.R, F = t.F, M = t.M, Cluster = predictions[i]
}).ToList();
ViewData["PredictedCustomers"] = predictedCustomers;
}
else if (!string.IsNullOrEmpty(download))
{
var businessData = calculatedScores.Select(x => new ClusteringData
{
R = x.R,
F = x.F,
M = x.M
}).ToList();
var predictions = segmentator.Predict(businessData);
var predictedCustomers = calculatedScores.Select((t, i) => new PredictionResult
{
CustomerId = t.CustomerId.ToString(), R = t.R, F = t.F, M = t.M, Cluster = predictions[i]
}).ToList();
ViewData["PredictedCustomers"] = predictedCustomers;
var groupedCustomers = predictedCustomers.GroupBy(x => x.Cluster);
ExcelPackage excel = new ExcelPackage();
foreach (var group in groupedCustomers)
{
var workSheet = excel.Workbook.Worksheets.Add("Cluster" + group.Key.ToString());
workSheet.TabColor = System.Drawing.Color.Black;
workSheet.DefaultRowHeight = 12;
//Header of table
//
workSheet.Row(1).Height = 20;
workSheet.Row(1).Style.HorizontalAlignment = ExcelHorizontalAlignment.Center;
workSheet.Row(1).Style.Font.Bold = true;
workSheet.Cells[1, 1].Value = "CustomerID";
workSheet.Cells[1, 2].Value = "R";
workSheet.Cells[1, 3].Value = "F";
workSheet.Cells[1, 4].Value = "M";
//Body of table
//
int recordIndex = 2;
foreach (var customer in group)
{
workSheet.Cells[recordIndex, 1].Value = customer.CustomerId;
workSheet.Cells[recordIndex, 2].Value = customer.R;
workSheet.Cells[recordIndex, 3].Value = customer.F;
workSheet.Cells[recordIndex, 4].Value = customer.M;
recordIndex++;
}
workSheet.Column(1).AutoFit();
workSheet.Column(2).AutoFit();
workSheet.Column(3).AutoFit();
workSheet.Column(4).AutoFit();
}
string excelName = "ClusteredData.xlsx";
using (var memoryStream = new MemoryStream())
{
excel.SaveAs(memoryStream);
var content = memoryStream.ToArray();
return(File(
content,
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
excelName));
}
//using (var memoryStream = new MemoryStream())
//{
// Response.ContentType = "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet";
// Response.Headers.Add("content-disposition", "attachment; filename=" + excelName + ".xlsx");
// excel.SaveAs(memoryStream);
// Response.OutputStream. memoryStream.WriteTo();
// Response.Flush();
// Response.End();
//}
}
}
return(null);
}
