# Non-time experiments
URL: https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/create-experiments/create-predictive/index.html

> Set basic and advanced options for creating predictive experiments; iterate quickly to evaluate and select the best predictive models.

# Non-time experiments

The following sections help to understand building atemporal (non-time) predictive models in Workbench.  See the section on [time-aware modeling](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/create-experiments/create-time-aware/index.html) for making forecasts with your data.

Predictive models can provide either supervised or unsupervised learning.

- Supervised learning uses the other features of your dataset to make predictions.
- Unsupervised learning uses unlabeled data to surface insights about patterns in your data, answering questions like "Are there anomalies in my data?" and "Are there natural clusters?"

| Topic | Description |
| --- | --- |
| Supervised experiment setup | Specify a target to build models using the other features of your dataset to make predictions. |
| Unsupervised experiment setup | Build clustering models that surface insights about patterns in your data or perform anomaly detection to identify outliers. |
| Advanced experiment setup | Use the Advanced settings tab to fine-tune experiment setup. |

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