Modeling details¶
This section provides details into components of the functionality that makes up the model building process.
| Topic | Description |
|---|---|
| Data | |
| Exploratory Data Analysis | Details of Exploratory Data Analysis (EDA), phases 1 and 2. |
| Data partitioning and validation | Describes validation types and data partitioning methods. |
| Modeling | |
| Modeling algorithms | List of supervised and unsupervised modeling algorithms supported by DataRobot. |
| Modeling process details | Bits and pieces of the initial model building process. |
| GPU support | Enabling GPU support to improve runtime for deep learning models. |
| Leaderboard reference | Components of the Leaderboard, blender models, and asterisked scores. |
| Model recommendation process | Steps involved in DataRobot's selection of a recommended model. |
| Sliced insights | View and compare insights based on segments of a project’s data. |
| SHAP reference | Details of SHapley Additive exPlanations, the coalitional game theory framework. |
| XEMP calculations | Describes the calculations used to determine XEMP qualitative strength. |
| Miscellaneous | |
| Optimization metrics | Short descriptions of all metrics available for model building. |
| AI Report | Create a report of modeling results and insights. |
| Export charts and data | Download created insights. |
| Worker Queue | Manage models and projects and export data. |