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);
}
