public TrainSSOMResponse GetTrainSSOM(TrainSSOMRequest request)
{
SSOM model = new SSOM(request.Width, request.Height, request.LearningRate, request.Epoch);
IReader reader = new CSVReader(System.Web.Hosting.HostingEnvironment.MapPath("~/App_Data/Iris.csv"));
model.GetData(reader);
foreach (var item in request.Labels)
{
model.Dataset.SetLabel(item);
}
model.FeatureLabel = request.FeatureLabel;
model.InitializeMap();
model.Train();
model.LabelNodes();
TrainSSOMResponse response = new TrainSSOMResponse()
{
Model = model
};
return(null);
}
public async Task <HttpResponseMessage> GetTrainSOM()
{
try
{
if (!Request.Content.IsMimeMultipartContent())
{
throw new HttpResponseException(HttpStatusCode.UnsupportedMediaType);
}
var root = HttpContext.Current.Server.MapPath(FILE_UPLOAD_PATH);
Directory.CreateDirectory(root);
var provider = new MultipartFormDataStreamProvider(root);
var result = await Request.Content.ReadAsMultipartAsync(provider);
var jsonModel = result.FormData["model"];
if (jsonModel == null)
{
throw new HttpResponseException(HttpStatusCode.BadRequest);
}
JObject parsedModel = JObject.Parse(jsonModel);
var epoch = (int)parsedModel["Epoch"];
var learningRate = (double)parsedModel["LearningRate"];
var height = (int)parsedModel["Height"];
var width = (int)parsedModel["Width"];
var kmeans = (int)parsedModel["KMeans"];
var k = (int)parsedModel["K"];
var regions = JsonConvert.DeserializeObject <List <Region> >(parsedModel["Regions"].ToString());
var csvFile = result.FileData.First();
SSOM model = new SSOM(width, height, learningRate, epoch, k);
model.Regions = regions;
var featureLabel = (string)parsedModel["FeatureLabel"];
var labels = ((string)parsedModel["Labels"]).Split(',').ToList();
IReader reader = new CSVReader(csvFile.LocalFileName);
model.GetData(reader);
foreach (var item in labels)
{
model.Dataset.SetLabel(item);
}
model.FeatureLabel = featureLabel;
model.InitializeMap();
model.Train();
model.LabelNodes();
IClusterer cluster = new KMeansClustering();
var flattenedMap = ArrayHelper <Node> .FlattenMap(model.Map);
var clusteredNodes = cluster.Cluster(flattenedMap, kmeans);
foreach (var node in clusteredNodes)
{
model.Map[node.Coordinate.X, node.Coordinate.Y].ClusterGroup = node.ClusterGroup;
}
FileInfo fileInfo = new FileInfo(csvFile.LocalFileName);
fileInfo.Delete();
TrainSOMResponse response = new TrainSOMResponse()
{
MapId = Guid.NewGuid(),
Model = model
};
var message = Request.CreateResponse(HttpStatusCode.OK, response);
File.Delete(result.FileData.First().LocalFileName);
return(message);
} catch (Exception ex)
{
var message = Request.CreateResponse(HttpStatusCode.InternalServerError, ex);
return(message);
}
}
public static void Program2(string[] args)
{
string filePath = @"C:\Users\Vilson\Desktop\Datasets\Kalaw-Dataset\config.json";
if (args.Length > 0)
{
filePath = args[0];
}
var content = System.IO.File.ReadAllText(filePath);
var config = ReadToObject(content);
// Build the Model
SSOM model = new SSOM(config.Width, config.Height, config.ConstantLearningRate, config.Epoch, config.K);
model.Regions = config.Regions;
// Subscribe to OnTrainingEvent
model.Training += _model_Training;
// Instantiate the reader
IReader _reader = new CSVReader(config.Dataset);
// Instantiate the clusterer
IClusterer clusterer = new KMeansClustering();
model.GetData(_reader);
// Get the labels
string[] labels = config.Labels.Split(',');
foreach (var label in labels)
{
model.Dataset.SetLabel(label);
}
// Set the feature label
model.FeatureLabel = config.FeatureLabel;
// Initialize the training
Stopwatch stopwatch = new Stopwatch();
Console.WriteLine("Start initializing map...");
stopwatch.Start();
model.InitializeMap();
stopwatch.Stop();
Console.WriteLine("Completed initialization...");
Console.WriteLine("Time elapsed: {0:hh\\:mm\\:ss}", stopwatch.Elapsed);
Console.WriteLine("Start training model...");
stopwatch.Restart();
model.Train();
stopwatch.Stop();
Console.WriteLine("Completed training model...");
Console.WriteLine("Time elapsed: {0:hh\\:mm\\:ss}", stopwatch.Elapsed);
Console.WriteLine("Start labelling node...");
stopwatch.Restart();
model.LabelNodes();
stopwatch.Stop();
Console.WriteLine("Completed labelling node...");
Console.WriteLine("Time elapsed: {0:hh\\:mm\\:ss}", stopwatch.Elapsed);
if (config.Clusters > 0)
{
Console.WriteLine("Start clustering nodes...");
stopwatch.Restart();
var flattenedMap = ArrayHelper <Node> .FlattenMap(model.Map);
var clusteredNodes = clusterer.Cluster(flattenedMap, config.Clusters);
foreach (var node in clusteredNodes)
{
model.Map[node.Coordinate.X, node.Coordinate.Y].ClusterGroup = node.ClusterGroup;
}
stopwatch.Stop();
Console.WriteLine("Completed clustering nodes...");
Console.WriteLine("Time elapsed: {0:hh\\:mm\\:ss}", stopwatch.Elapsed);
}
// Export the model
Console.WriteLine("Exporting model...");
var guid = Guid.NewGuid();
model.MapId = guid;
model.Dataset = null;
var serializeObject = JsonConvert.SerializeObject(model, Formatting.Indented);
string exportFileName = string.Format("{0}Map_{1}.json", config.Export, guid);
System.IO.File.WriteAllText(exportFileName, serializeObject);
Console.WriteLine("Training completed...");
Console.ReadLine();
}
