Clustering for segmented modeling¶

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:

• Create a clustering model as part of a segmented modeling run.

• Create a clustering model and save it to the Model Registry to be used for a later segmented modeling run.

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.

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.

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.