This page will help you get started with using the datarobot R package to interact with DataRobot. You can import data, build models, evaluate metrics, and make predictions right from the R console.
There are several advantages to interacting with DataRobot programmatically:
You can find the full documentation of the datarobot R package here.
You can access code samples on our public DataRobot Community github. This section lists the currently available samples and provides links to the related GitHub locations.
The API endpoint you specify for accessing DataRobot is dependent on the deployment environment, as follows:
DataRobot API highlights to go through.
API TrainingPrediction Explanations ClusteringAdvanced Feature SelectionTime Series Model FactoryModel Factory with Readmissions Dataset
Learn how to get started with R and DataRobot by importing data and starting a project.
Starting a Binary Classification ProjectStarting a Multiclass Classification ProjectStarting a Regression ProjectStarting a TIme Series ProjectStarting a Project with Selected Blueprints
Learn how to customize components of the modeling process.
Advanced TuningDatetime Partitioning
Learn how to export and visualize key metrics for evaluating and interpreting your models.
Getting Confusion ChartGetting Feature ImpactGetting Lift ChartGetting ROC CurveGetting Word Cloud
Learn how to download full documentation files for the models you created.
Getting Compliance Documentation
Learn how to manipulate feature lists and do advanced feature selection.
Advanced Feature SelectionFeature Lists ManipulationsTransforming Feature Types
Learn how to make predictions in DataRobot from R.
Getting Predictions from Prediction Explanations
Learn how to manage and monitor your models.
Model Management and Monitoring
Explore end-to-end use cases for integrating R and DataRobot.
Detecting Droids with DataRobotHospital ReadmissionsModel factory with Readmissions DatasetTime Series Model factoryLead Scoring on Bank Marketing Data