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Creating a Related Sequence Clustering Model (Intermediate Data Mining Tutorial)

Through your exploration of the sequence clustering model, you learned that other attributes such as Region or Income have a strong effect on the models; therefore, to understand the sequences better, you will create a related sequence clustering model and remove the attributes related to customer demographics.

In this task, you will create a copy of the regional sequence clustering model, and then remove from the model any columns that are not directly related to the sequences.

The new model will contain all the same columns as the mining model on which it is based. However, you do not need to remove the columns from the mining structure, only specify that the new mining model ignore the columns.

To make a copy of the sequence clustering model

  1. In SQL Server Data Tools (SSDT), in the Data Mining Designer, click the Mining Models tab.

  2. Right-click the model you want to copy, and select New Mining Model.

  3. In the New Mining Model dialog box, type a model name, and select Microsoft Sequence Clustering.

    For this tutorial, type the name Sequence Clustering.

  4. Click OK.

To remove columns from the mining model

  1. In the Mining Model tab, in the column for the new model named Sequence Clustering, click the row for the Income Group attribute, and select Ignore.

  2. Repeat this step for the attribute Region.

  3. Click the plus sign next to the table name, v Assoc Seq Line Items, to expand the table and view the columns from the nested table.

    The new model should have only the following columns:

    Order Number    Key

    Line Number     Key

    Model     Predict

To process the new sequence clustering model

  1. In the Mining Model tab, right-click the new model named Sequence Clustering, and select Process Model.

    Because the new simplified mining model is based on a structure that has already been processed, you do not need to reprocess the structure. You can process just the new mining model.

  2. Click Yes to deploy the updated data mining project to the server.

  3. In the Process Mining Model dialog box, click Run.

  4. Click Close to close the Process Progress dialog box, and then click Close again in the Process Mining Model dialog box.

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