public static async Task <HttpResponseMessage> CreateSingleStructurePridiction(this OsdrWebClient client, RunSingleStructurePrediction ssp) { var postParameters = JsonConvert.SerializeObject(ssp); var response = await client.PostData("api/machinelearning/predictions/structure", postParameters); return(response); }
public static async Task <HttpResponseMessage> MachineLearningPredict(this OsdrWebClient client, Guid parentId, Guid modelBlobId, Guid datasetBlobId, Guid userId, string datasetBucket, Guid modelBucket, string folderName) { var postData = $@" {{ 'TargetFolderId': '{parentId}', 'DatasetBlobId': '{datasetBlobId}', 'DatasetBucket': '{datasetBucket}', 'ModelBlobId': '{modelBlobId}', 'ModelBucket': '{modelBucket}', 'UserId': '{userId}' }}" ; return(await client.PostData("/api/machinelearning/predictions", postData)); }
public static async Task <HttpResponseMessage> MachineLearningTrain(this OsdrWebClient client, Guid sourceBlobId, string sourceBucket, Guid userId, Guid parentId, bool optimize) { var folderId = Guid.NewGuid(); var createMLModel = new CreateMachineLearningModel { TargetFolderId = folderId, SourceBlobId = sourceBlobId, Scaler = "some sting named as Scaler", SourceBucket = sourceBucket, UserId = userId, SourceFileName = "combined lysomotrophic.sdf", Methods = new List <string> { "NaiveBayes" }, TrainingParameter = "Soluble", SubSampleSize = 1, TestDataSize = new decimal(.1), KFold = 2, ModelType = "Classification", Fingerprints = new List <Fingerprint> { new Fingerprint { Type = "ecfp", Radius = 2, Size = 512 } }, Optimize = optimize }; var postParameters = JsonConvert.SerializeObject(createMLModel); var response = await client.PostData("/api/machinelearning/models", postParameters); return(response); }
public static async Task <HttpResponseMessage> CreateFolderEntity(this OsdrWebClient client, Guid parentNodeId, string name) { return(await client.PostData("api/entities/folders", $"{{'Name': '{name}', parentId: '{parentNodeId}'}}")); }
public static async Task <HttpResponseMessage> MachineLearningCreate(this OsdrWebClient client, Guid parentNodeId, string name) { return(await client.PostData("/api/machinelearning/predictions", $"{{'Name': '{name}', parentId: '{parentNodeId}'}}")); }