public void Test_Save() { double[][] clusterCenters = new double[3][]; clusterCenters[0] = new double[] { 5.0, 5.0 }; clusterCenters[1] = new double[] { 15.0, 15.0 }; clusterCenters[2] = new double[] { 30.0, 30.0 }; string[] attributes = new string[] { "Height", "Weight" }; int numAttributes = attributes.Length; // 2 in this demo (height,weight) int numClusters = 3; // vary this to experiment (must be between 2 and number data tuples) int maxCount = 300; // trial and error ClusteringSettings settings = new ClusteringSettings(maxCount, numClusters, numAttributes, KmeansAlgorithm: 2); // Creates learning api object LearningApi api = new LearningApi(loadDescriptor()); // creates data var rawData = Helpers.CreateSampleData(clusterCenters, 2, 10000, 0.5); KMeansAlgorithm kMeans = new KMeansAlgorithm(settings); // train var response = kMeans.Run(rawData, api.Context); string fileName = "Test01.json"; kMeans.Save(rootFolder + fileName); }