示例#1
0
        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);
        }
示例#2
0
        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);
            }
        }
示例#3
0
        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();
        }