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.