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Clustering for segmented modeling

Availability information

Clustering for segmented modeling, available as a public preview feature, is off by default. Contact your DataRobot representative or administrator for information on enabling the feature.

Feature flag: Enable Clustering Project Type for Time Series

To perform time series segmented modeling, you need to define segments for your dataset. Instead of doing this yourself, you can create a DataRobot clustering model that discovers appropriate segments for you. To do this, you can:

Build a segmented model using clusters as segments

The following workflow shows how to build a clustering model and use the generated clusters as segments in a segmented modeling project:

  1. Set up a time series project as normal, enter the target and series ID for the segmented project, then click the pencil next to Segmentation method.

  2. Under How are the segments defined, click New clustering model and click time series clustering in the paragraph below.

    DataRobot sets up a time-aware clustering project—an unsupervised project with the Clusters option enabled.

  3. For Which feature should DataRobot use to segment the series, include the target feature for the segmented modeling project. In this example, the target feature is Sales. The required features—the date/time feature (Date) and the series ID feature (Store)—are populated in the text box, as well.

  4. Click Start to generate the clustering models. DataRobot leverages the clustering models to define segments in the segmented modeling project.

  5. After the run completes, select a model from the Leaderboard and click Predict > Use for Segmentation. On this tab, you can create a segmented modeling project that uses the clusters to help define the segments.

  6. For What would you like the new project to predict, enter the target feature for the segmented modeling project.

  7. Click Create project and save to Model Registry.

    To save the clustering model and create the project later

    Instead of creating a segmentation project now, you can save the clustering model as a model package by selecting Save to Model Registry.

    Later you can build a segmented modeling project using the clustering model.

  8. Click Go to project.

    Your segmentation method is configured with the clustering model.

  9. Click Start to build your segmented model. At the prompt, confirm that you want to run a segmentation project.

    After modeling is complete, a Combined Model displays on the Leaderboard. You can explore the results and the segment models.

Tip

This procedure saves the time series clustering model as a model package. You can later create new segmented modeling projects using the saved clustering model package.

Build a segmented model using a saved clustering model

After you save a time series clustering model as a model package, you can use it in a new segmented modeling project.

Note

You must use the same dataset for the segmented modeling project that you used to generate the clustering project.

  1. Set up a time series project as normal, enter the target and series ID for the segmented project, then click the pencil next to Segmentation method.

  2. Under How are the segments defined, click Existing clustering model and click + Browse model registry below.

  3. Select a time series clustering model package from the list and click Select model package.

  4. Click Set segmentation method.

  5. Click Start to build your segmented model. At the prompt, confirm that you want to run a segmentation project.

    After modeling is complete, a Combined Model displays on the Leaderboard. You can explore the results and the segment models.


Updated June 1, 2022
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