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public CreateDataset ( |
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| arguments | ||
| return | Task |
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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);
}
