GetBlenderModelFromJobId | R Documentation |
The function RequestBlender initiates the creation of new blender models in a DataRobot project.
GetBlenderModelFromJobId(project, modelJobId, maxWait = 600)
project |
character. Either (1) a character string giving the unique alphanumeric identifier for the project, or (2) a list containing the element projectId with this identifier. |
modelJobId |
integer. The integer returned by RequestBlender. |
maxWait |
integer. The maximum time (in seconds) to wait for the model job to complete. |
It submits requests to the DataRobot modeling engine and returns an integer-valued modelJobId. The GetBlenderModelFromJobId function polls the modeling engine until the model has been built or a specified time limit is exceeded, returning an S3 object of class 'dataRobotBlenderModel' when the model is available.
Motivation for this function is the fact that some models - e.g., very complex machine learning models fit to large datasets - may take a long time to complete. Splitting the model creation request from model retrieval in these cases allows the user to perform other interactive R session tasks between the time the model creation/update request is made and the time the final model is available.
An S3 object of class ‘dataRobotBlenderModel’ summarizing all available information about the model. It is a list with the following components:
modelId. character. The unique alphanumeric blender model identifier.
modelNumber. integer. The assigned model number.
modelType. character. The type of model, e.g. 'AVG Blender'.
modelIds. character. List of unique identifiers for the blended models.
blenderMethod. character. The blender method used to create this model.
featurelistId. character. Unique alphanumeric identifier for the featurelist on which the model is based.
processes. character. Components describing preprocessing; may include modelType.
featurelistName. character. Name of the featurelist on which the model is based.
blueprintId. character. The unique blueprint identifier on which the model is based.
samplePct. numeric. The percentage of the dataset used in training the
model. For projects that use datetime partitioning, this will be NA. See
trainingRowCount
instead.
trainingRowCount. integer. Number of rows of the dataset used in
training the model. For projects that use datetime partitioning, if
specified, this defines the number of rows used to train the model and
evaluate backtest scores; if unspecified, either trainingDuration
or trainingStartDate
and trainingEndDate
was used instead.
isFrozen. logical. Was the model created with frozen tuning parameters?
metrics. list. The metrics associated with this model. Each element is a list with elements for each possible evaluation type (holdout, validation, and crossValidation).
modelCategory. character. The category of model (e.g., blend, model, prime).
projectId. character. Unique alphanumeric identifier for the project.
projectName. character. Name of the project.
projectTarget. character. The target variable predicted by all models in the project.
projectMetric. character. The fitting metric optimized by all project models.
## Not run:
projectId <- "59a5af20c80891534e3c2bde"
modelsToBlend <- c("5996f820af07fc605e81ead4", "59a5ce3301e9f0296721c64c")
blendJobId <- RequestBlender(projectId, modelsToBlend, "GLM")
GetBlenderModelFromJobId(projectId, blendJobId)
## End(Not run)
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