k-Means Model Viewer

This selection displays a successfully built k-Means model (a clustering model).

Menus

The following menus appear when the model is displayed in a new window:

Tabs

The model viewer the following tabs:

Build Settings

This tab displays the Type of the model (Clustering), the Algorithm used to build the model (k-means), the Algorithm Settings used to build the model, and the Attributes used to build the model.

Oracle Data Mining 11g models can be built using Automatic Data Preparation (ADP). If the model was built using ADP, then Automatic Data Preparation has the value yes.

The following settings are displayed:

For information about the settings, see k-Means Settings.

The attributes are listed in the Attributes grid; the following information is displayed for each attribute:

To save the information about the attributes as a text file, click the Save As icon (a yellow arrow above a graphic of a page).

Clusters

To see the clusters, click the Clusters tab.

The following constants are displayed:

You can display either all clusters (the default) or leaf clusters only. If you display all clusters, you can see how and why the splits were created in the iterative process. To see the final clusters, click the Show Leaves Only checkbox.

For each cluster, the Cluster ID and number of Cases are displayed.

To see the cluster details, including attribute histograms, select a cluster, and click the Detail button. For more about the detail display, see Cluster Details.

You can also expand and collapse all cluster tree nodes by clicking the appropriate buttons.

To save the information about the clusters as a text file, click the Save As icon (a yellow arrow above a graphic of a page).

Results

To see results, click the Results tab.

The tab contains a tree view of results. To view specific results, select the result, and click View. To delete a result, select one or more of the results and click Delete.

Rules

To see the rules, click the Rules tab.

You can display either rules for all clusters (the default) or rules for leaf clusters only. To display rules for leaf clusters only, click the Only Show Rules For Leaf Clusters checkbox. You can also reduce the complexity of rules by limiting the attributes included in rules to the most important attributes. To limit the attributes included in rules, click the Only Show Attributes with Minimum Relevance Rank checkbox, and specify the minimum relevance rank. The default minimum relevance rank is 10. For a description of relevance rank, see Relevance Rank. After you change either of these items, click Refresh to display the rules that satisfy the specified requirements.

Click Scale to calculate new values of PROVIDE. The button changes to Unscale.

The rules are displayed in a grid. To view a detailed display of a rule, select the rule; the detailed rule is displayed in the Rule detail area. For each rule, If (condition) and Then (cluster) are displayed.

To sort the rules, click Sort.

The following is displayed for each rule:

Note: In rare circumstances, no rules may be displayed for a cluster. In this case, you can generate rules by lowering Minimum Support and rebuilding the model. See the discussion of Minimum Support in k-Means Settings for details.

Support and confidence can be used to rank the rules and hence the predictions.

Task

This tab describes the task used to build the model. It shows when the task ran, what input was used, and what output was created.