Modifying the Targeted Mailing Model (Data Mining Tutorial)
The initial mining structure that you created in the previous task contains a single mining model that is based on the Microsoft Decision Trees algorithm. In this task, you will define two additional models by using the Mining Models tab of Data Mining Designer. In this task you will define a Naive Bayes model and a Clustering model.
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Data Mining Designer, Managing Mining Models in Data Mining Designer, Microsoft Clustering Algorithm, Microsoft Naive Bayes Algorithm
Creating a Microsoft Clustering Model
To create a clustering mining model
Switch to the Mining Models tab in Data Mining Designer in Business Intelligence Development Studio.
Notice that the designer displays two columns, one for the mining structure and one for the initial mining model, which you created in the previous task in this lesson.
Right-click the Structure column and select New Mining Model.
The New Mining Model dialog box opens.
In Model name, type TM_Clustering.
In Algorithm name, select Microsoft Clustering.
Click OK.
A new model appears in the Mining Models tab of Data Mining Designer. A model that is built with the Microsoft Clustering algorithm can cluster and predict continuous and discrete attributes. Although you can modify the column usage and properties for the new model, no changes are required for the TM_Clustering model for this tutorial.
Creating a Microsoft Naive Bayes Model
To create a Naive Bayes model
In the Mining Models tab of Data Mining Designer, right-click the Structure column, and select New Mining Model.
The New Mining Model dialog box opens.
In Model name, type TM_NaiveBayes.
In Algorithm name, select Microsoft Naive Bayes. Click OK.
A message appears explaining that the Microsoft Naive Bayes algorithm does not support columns that are continuous. To work with these columns in the Naive Bayes model, you must discretize them. For this tutorial, you will just ignore the columns.
Click Yes to acknowledge the message and continue.
A new model appears in the Mining Models tab. Although you can modify the column usage and properties for all the models in this tab, no changes are required for the TM_NaiveBayes model for this tutorial.
Processing the Mining Models
Now that the structure and parameters for the mining models are complete, you can deploy and process the models. You can either process a specific mining model that is associated with a mining structure or you can process all the models that are associated with the structure.
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Processing Data Mining Objects
To deploy the project and process a selected mining model
In the Mining Model menu of BI Development Studio, select a mining model from the one or more columns of models in the grid.
On the Mining Model menu, select Process Model.
If you made changes to the mining structure, you will be prompted to redeploy the structure before processing the model. Click Yes.
Click Run in the Processing Mining Structure - Targeted Mailing dialog box.
The Process Progress dialog box opens to display the details of model processing. Model processing might take some time, depending on your computer.
Click Close in the Process Progress dialog box after the models have completed processing.
Click Close in the Processing Mining Structure - <structure> dialog box..
The Analysis Services database is deployed to the server computer, and the mining model is processed.
If the database has already been deployed to the server computer, you can process just the mining models by using the following process.
To process the mining models when the project has already been deployed
On the Mining Model menu of BI Development Studio, click Process Mining Structure and All Models.
The Process Mining Structure - <Targeted Mailing> dialog box opens.
Click Run.
The Process Progress dialog box opens to display information about model processing. Model processing may take some time, depending on your computer.
After processing is complete, click Close in the Process Progress and Process Mining Structure - <Targeted Mailing> dialog boxes.
Next Task in Lesson
Exploring the Targeted Mailing Models (Data Mining Tutorial)