Advanced options¶
After importing data and selecting a target variable, the Data page appears. From this page you can click the Show advanced options link to access advanced modeling parameters.
These parameters are summarized in the following sections:
Option | Description |
---|---|
Additional | Set additional parameters and modify values that can effect model builds. |
Bias and Fairness | Set conditions that help calculate fairness, as well as identify and attempt to mitigate bias in a model's predictive behavior. |
Clustering | Set the number of clusters that DataRobot discovers in a time series clustering project. |
External model prediction insights | Bring external model(s) into the DataRobot AutoML environment, view them on the Leaderboard, and run a subset of DataRobot's evaluative insights for comparison against DataRobot models. |
Feature Constraints | Set monotonic constraints to control the influence between variables and target. |
Partitioning | Set how data is partitioned for training/validation/holdout and the validation type. |
Partitioning: Date/time | Set how data is partitioned for OTV or time series projects. |
Smart Downsampling | Downsample the majority class for faster model build time. |
Time Series | Set a variety or time series-specific advanced options. |
Train-time image augmentation | Create new training images to increase the amount of training data. |
Updated December 6, 2024
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