public Insert2 GetModelStatus(ProjectModelId projectModelId)
{
var getRequest = PredictionService.Trainedmodels.Get(projectModelId.ProjectNumber, projectModelId.ModelId);
Insert2 response = getRequest.Execute();
return(response);
}
public string DeleteTrainedModel(ProjectModelId projectModelId)
{
var deleteRequest = PredictionService.Trainedmodels.Delete(projectModelId.ProjectNumber, projectModelId.ModelId);
string deleteResponse = deleteRequest.Execute();
return(deleteResponse);
}
public Insert2 TrainRegressionModel(ProjectModelId projectModelId, string csvDataPathInStorage)
{
Insert insertBody = new Insert
{
StorageDataLocation = csvDataPathInStorage,
Id = projectModelId.ModelId,
ModelType = "REGRESSION",
};
TrainedmodelsResource.InsertRequest insertRequest = PredictionService.Trainedmodels.Insert(insertBody, projectModelId.ProjectNumber);
Insert2 insertResponse = insertRequest.Execute();
return insertResponse;
}
public Insert2 TrainRegressionModel(ProjectModelId projectModelId, string csvDataPathInStorage)
{
Insert insertBody = new Insert
{
StorageDataLocation = csvDataPathInStorage,
Id = projectModelId.ModelId,
ModelType = "REGRESSION",
};
TrainedmodelsResource.InsertRequest insertRequest = PredictionService.Trainedmodels.Insert(insertBody, projectModelId.ProjectNumber);
Insert2 insertResponse = insertRequest.Execute();
return(insertResponse);
}
static void Main()
{
PredictionFramework predictionFramework = new PredictionFramework();
predictionFramework.CreatePredictionService(AUTH_JSON_FILE);
ProjectModelId projectModelId = new ProjectModelId(PROJECT_NUMBER, "sin-360-sanity");
//ICommand command = new TrainingCommand(predictionFramework, projectModelId, "sanity-test-cases/sin-360-training-data.csv");
//ICommand command = new StatusCommand(predictionFramework, projectModelId);
//ICommand command = new AnalysisCommand(predictionFramework, projectModelId);
ICommand command = new PredictCommand(predictionFramework, projectModelId, @"D:\@Temp\ML_Feasibility\Tech.Sugar-ML-in-Cloud\GCPDemo\predict-data.csv");
Console.WriteLine("Project number: {0}, Model ID: {1}", projectModelId.ProjectNumber, projectModelId.ModelId);
Console.WriteLine("Command: {0}", command.Command);
command.Run();
}
// //const string AUTH_JSON_FILE = @"D:\@Temp\@Issues\2018-01-10_Igor_ML\data\google\data1p1x7-b93dbc2c7b4b.json";
// private const string AUTH_JSON_FILE = @"D:\@Temp\@Issues\2018-01-10_Igor_ML\data\google\HAR Machine Learning-2a2ea6fd74e3.json";
// private const string PROJECT_NUMBER = "1024476357063";
// private const string modelId = "data1x1p7";
// private const string storageData = "sanity-test-cases/data_1_gcp.csv";
//// private const string predictFile = @"D:\@Temp\@Issues\2018-01-10_Igor_ML\data\data_1_gcp_predict.csv";
static void Main()
{
PredictionFramework predictionFramework = new PredictionFramework();
predictionFramework.CreatePredictionService(AUTH_JSON_FILE);
ProjectModelId projectModelId = new ProjectModelId(PROJECT_NUMBER, modelId);
//ICommand command = new TrainingCommand(predictionFramework, projectModelId, storageData);
//ICommand command = new StatusCommand(predictionFramework, projectModelId);
//ICommand command = new AnalysisCommand(predictionFramework, projectModelId);
ICommand command = new PredictCommand(predictionFramework, projectModelId, predictFile);
Console.WriteLine("Project number: {0}, Model ID: {1}", projectModelId.ProjectNumber, projectModelId.ModelId);
Console.WriteLine("Command: {0}", command.Command);
command.Run();
}
public Insert2 GetModelStatus(ProjectModelId projectModelId)
{
var getRequest = PredictionService.Trainedmodels.Get(projectModelId.ProjectNumber, projectModelId.ModelId);
Insert2 response = getRequest.Execute();
return response;
}
public string DeleteTrainedModel(ProjectModelId projectModelId)
{
var deleteRequest = PredictionService.Trainedmodels.Delete(projectModelId.ProjectNumber, projectModelId.ModelId);
string deleteResponse = deleteRequest.Execute();
return deleteResponse;
}
