This function returns a DataRobot S3 object of class dataRobotModel for the model defined by project and modelId.
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.
character. Unique alphanumeric identifier for the model of interest.
The S3 object returned by this function is required by the functions DeleteModel, ListModelFeatures, and RequestSampleSizeUpdate.
An S3 object of class ‘dataRobotModel’, which is a list with the following components:
featurelistId. Character string: unique alphanumeric identifier for the featurelist on which the model is based.
processes. Character vector with components describing preprocessing; may include modelType.
featurelistName. Character string giving the name of the featurelist on which the model is based.
projectId. Character string giving the unique alphanumeric identifier for the project.
samplePct. Numeric or NULL. The percentage of the project dataset used in training the
model. If the project uses datetime partitioning, the
samplePct will be NULL.
trainingRowCount. Integer. The number of rows of the project dataset used in training
the model. In a datetime partitioned project, if specified, defines the number of
rows used to train the model and evaluate backtest scores; if unspecified, either
trainingEndDate was used to
determine that instead.
isFrozen. Logical : is model created with frozen tuning parameters.
modelType. Character string describing the model type.
metrics. List with one element for each valid metric associated with the model. Each element is a list with elements for each possible evaluation type (holdout, validation, and crossValidation).
modelCategory. Character string giving model category (e.g., blend, model).
blueprintId. Character string giving the unique DataRobot blueprint identifier on which the model is based.
modelId. Character string giving the unique alphanumeric model identifier.
modelNumber. Integer. The assigned model number.
projectName. Character string: optional description of project defined by projectId.
projectTarget. Character string defining the target variable predicted by all models in the project.
projectMetric. Character string defining the fitting metric optimized by all project models.
supportsMonotonicConstraints logical. Whether or not the model supports monotonic constraints.
monotonicIncreasingFeaturelistId character. The ID of the featurelist specifying the
features that are constrained to be monotonically increasing. Will be
NULL if no
increasing constraints are used.
monotonicDecreasingFeaturelistId character. The ID of the featurelist specifying the
features that are constrained to be monotonically decreasing. Will be
NULL if no
decreasing constraints are used.
isStarred logical. Whether or not the model is starred.
predictionThreshold numeric. For binary classification projects, the threshold used for predictions.
predictionThresholdReadOnly logical. Whether or not the prediction threshold can be modified. Typically, the prediction threshold can no longer be modified once a model has a deployment created or predictions have been made with the dedicated prediction API.
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## Not run: projectId <- "59a5af20c80891534e3c2bde" modelId <- "5996f820af07fc605e81ead4" GetModel(projectId, modelId) ## End(Not run)
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