GetBlenderModel {datarobot}

Retrieve the details of a specified blender model

Description

This function returns a DataRobot S3 object of class dataRobotModel for the model defined by project and modelId.

Usage

GetBlenderModel(project, modelId)

Arguments

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.

modelId

character. Unique alphanumeric identifier for the blender model of interest.

Value

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.

Examples

## Not run: 
  projectId <- "59a5af20c80891534e3c2bde"
  modelId <- "5996f820af07fc605e81ead4"
  GetBlenderModel(projectId, modelId)

## End(Not run)