DataRobot Python Package¶
- Getting Started
- Configuration
- QuickStart
- Datasets
- Projects
- Datetime Partitioned Projects
- Time Series Projects
- Visual AI Projects
- Unsupervised Projects (Anomaly Detection)
- Creating Unsupervised Projects
- Creating Time Series Unsupervised Projects
- Unsupervised Project Metrics
- Estimating Accuracy of Unsupervised Anomaly Detection Datetime Partitioned Models
- Explaining Unsupervised Time Series Anomaly Detection Models Predictions
- Assessing Unsupervised Anomaly Detection Models on External Test Set
- Requesting External Scores and Insights (Time Series)
- Requesting External Scores and Insights for AutoML models
- Retrieving External Scores and Insights
- Blueprints
- Models
- Start Training a Model
- List Finished Models
- Retrieve a Known Model
- Train a Model on a Different Sample Size
- Cross-Validating a Model
- Find the Features Used
- Feature Impact
- Feature Effects
- Predict new data
- Model IDs Vs. Blueprint IDs
- Model parameters
- Create a Blender
- Lift chart retrieval
- ROC curve retrieval
- Residuals chart retrieval
- Word Cloud
- Scoring Code
- Get a model blueprint chart
- Get a model missing values report
- Get a blueprint documentation
- Request training predictions
- Advanced Tuning
- SHAP Impact
- Number of Iterations Trained
- Jobs
- ModelJobs
- Predictions
- Prediction Explanations
- Batch Predictions
- Batch Prediction Job Definitions
- DataRobot Prime
- Rating Table
- Training Predictions
- Monotonic Constraints
- Database Connectivity
- Model Recommendation
- Sharing
- Deployments
- Custom Models
- Custom Tasks
- Compliance Documentation
- Compliance Documentation Template
- Automated Documentation
- Credentials
- External Testset
- Feature Discovery
- Register Primary Dataset to start Project
- Register Secondary Dataset(s) in AI Catalog
- Create Dataset Definitions and Relationships using helper functions
- Create Relationships Configuration
- Create Feature Discovery Project
- Start Training a Model
- Create Secondary Datasets Configuration for prediction
- Perform Prediction over trained model
- Relationships Configuration
- Secondary Dataset Config
- API Reference
- Advanced Options
- Anomaly Assessment
- Batch Predictions
- Blueprint
- Calendar File
- Automated Documentation
- Compliance Documentation Templates
- Compliance Documentation
- Confusion Chart
- Credentials
- Custom Models
- Custom Tasks
- Database Connectivity
- Datasets
- Datetime Trend Plots
- Deployment
- External Scores and Insights
- Feature
- Feature Association
- Feature Association Matrix Details
- Feature Association Featurelists
- Feature Discovery
- Feature Effects
- Feature Fit
- Feature List
- Job
- Lift Chart
- Missing Values Report
- Models
- ModelJob
- Pareto Front
- Partitioning
- PayoffMatrix
- PredictJob
- Prediction Dataset
- Prediction Explanations
- Predictions
- PredictionServer
- PrimeFile
- Project
- Rating Table
- Reason Codes (Deprecated)
- Recommended Models
- ROC Curve
- Ruleset
- SHAP
- SharingAccess
- Training Predictions
- VisualAI
- Word Cloud
- Examples
- Changelog
- 2.26.1
- 2.26.0
- 2.25.0
- 2.24.0
- 2.23.0
- 2.22.1
- 2.21.0
- 2.20.0
- 2.19.0
- 2.18.0
- 2.17.0
- 2.16.0
- 2.15.1
- 2.15.0
- 2.14.2
- 2.14.1
- 2.14.0
- 2.13.0
- 2.12.0
- 2.11.0
- 2.9.0
- 2.8.1
- 2.8.0
- 2.7.2
- 2.7.1
- 2.7.0
- 2.6.1
- 2.6.0
- 2.5.1
- 2.5.0
- 2.4.0
- 2.3.0
- 2.2.33
- 2.2.32
- 2.1.31
- 2.1.30
- 2.1.29
- 2.1.28
- 2.0.27
- 0.2.26
- 0.2.25
- 0.2.24
- 0.1.24
- 0.1.23
- 0.1.22
- 0.1.21
- 0.1.20
- 0.1.19
- 0.1.18
- 0.1.17
- 0.1.16
- 0.1.15
- 0.1.14
- 0.1.13
- 0.1.12
- 0.1.11
- 0.1.10
- 0.1.9