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:
|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 September 27, 2022
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