GetModel: Retrieve the details of a specified model

View source: R/Models.R

GetModelR Documentation

Retrieve the details of a specified model

Description

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

Usage

GetModel(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 model of interest.

Details

The S3 object returned by this function is required by the functions DeleteModel, ListModelFeatures, and RequestSampleSizeUpdate.

Value

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. See trainingRowCount, trainingDuration, and trainingStartDate and trainingEndDate instead.

  • 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 trainingDuration or trainingStartDate and 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.

Examples

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

## End(Not run)

datarobot documentation built on May 6, 2022, 5:06 p.m.