public CreateDataset ( |
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arguments | ||
Результат | Task |
public async Task CreateMultiDataset() { Client c = new Client(userName, apiKey); Source.Arguments args = new Source.Arguments(); args.Add("remote", "https://static.bigml.com/csv/iris.csv"); args.Add("name", "https://static.bigml.com/csv/iris.csv"); Source s = await c.CreateSource(args); s = await c.Wait<Source>(s.Resource); Assert.AreEqual(s.StatusMessage.StatusCode, Code.Finished); DataSet.Arguments argsDS = new DataSet.Arguments(); argsDS.Source = s.Resource; DataSet ds = await c.CreateDataset(argsDS); ds = await c.Wait<DataSet>(ds.Resource); // use the other DataSet constructor argsDS = new DataSet.Arguments(s); DataSet ds2 = await c.CreateDataset(argsDS); ds2 = await c.Wait<DataSet>(ds2.Resource); argsDS = new DataSet.Arguments(); argsDS.OriginDatasets.Add(ds.Resource); argsDS.OriginDatasets.Add(ds2.Resource); argsDS.Name = "Dataset using multi datasets"; DataSet dsMulti = await c.CreateDataset(argsDS); dsMulti = await c.Wait<DataSet>(dsMulti.Resource); await c.Delete(s); await c.Delete(ds); await c.Delete(ds2); await c.Delete(dsMulti); }
/// <summary> /// Simple sample that runs through all steps to explicitly create a /// local prediction from a csv file with the classic iris data. /// </summary> static async Task MainAsync() { // New BigML client with username and API key Console.Write("user: "******"key: "); var ApiKey = Console.ReadLine(); var client = new Client(User, ApiKey); // New source from in-memory stream, with separate header. That's the header var source = await client.CreateSource(iris, "Iris.csv", "sepal length, sepal width, petal length, petal width, species"); // No push, so we need to busy wait for the source to be processed. while ((source = await client.Get(source)).StatusMessage.NotSuccessOrFail()) { await Task.Delay(10); } Console.WriteLine(source.StatusMessage.ToString()); // Default dataset from source var dataset = await client.CreateDataset(source); // No push, so we need to busy wait for the dataset to be processed. while ((dataset = await client.Get(dataset)).StatusMessage.NotSuccessOrFail()) { await Task.Delay(10); } Console.WriteLine(dataset.StatusMessage.ToString()); // Default model from dataset var model = await client.CreateModel(dataset); // No push, so we need to busy wait for the source to be processed. while ((model = await client.Get(model)).StatusMessage.NotSuccessOrFail()) { await Task.Delay(10); } Console.WriteLine(model.StatusMessage.ToString()); Console.WriteLine("Creating local model"); Dictionary<string, dynamic> inputData = new Dictionary<string, dynamic>(); inputData.Add("000002", 3); inputData.Add("000003", 1.5); var localModel = model.ModelStructure(); var nodeResult = localModel.predict(inputData); Console.WriteLine("Predict:\n" + nodeResult); }
public async Task CreateDataset() { Client c = new Client(userName, apiKey); Source.Arguments args = new Source.Arguments(); args.Add("remote", "https://static.bigml.com/csv/iris.csv"); Source s = await c.CreateSource(args); s = await c.Wait<Source>(s.Resource); Assert.AreEqual(s.StatusMessage.StatusCode, Code.Finished); DataSet.Arguments argsDS = new DataSet.Arguments(); DataSet ds = await c.CreateDataset(argsDS); ds = await c.Wait<DataSet>(ds.Resource); await c.Delete(s); await c.Delete(ds); }