---
title: Advanced options
description: Set advanced parameters before building models to set non-default characteristics of the model build.

---

# Advanced options {: #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](additional)  | Set additional parameters and modify values that can effect model builds.   
[Bias and Fairness](fairness-metrics)  | Set conditions that help calculate fairness, as well as identify and attempt to mitigate bias in a model's predictive behavior.  
[Clustering](time-series-cluster-adv-opt.md) | Set the number of clusters that DataRobot discovers in a time series clustering project.
[External model prediction insights](external-preds) | 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](feature-con)  | Set monotonic constraints to control the influence between variables and  target.
[Partitioning](partitioning)  | Set how data is partitioned for training/validation/holdout and the validation type.
Partitioning: Date/time  | Set how data is partitioned for [OTV](otv#advanced-options) or [time series](ts-date-time) projects.
[Smart Downsampling](smart-ds)  | Downsample the majority class for faster model build time.  
[Time Series](ts-adv-opt)   | Set a variety or time series-specific advanced options.
[Train-time image augmentation](ttia)  | Create new training images to increase the amount of training data.


![](images/advanced-options-link.png)
