Sequence Clustering Cluster Transition Tab (Mining Model Viewer)


Applies To: SQL Server 2016

The State Transitions tab in the Microsoft Sequence Clustering Viewer provides a closer look at the transitions between attribute-value pairs, or states, in the selected cluster.

Use this view of a sequence clustering model to view patterns. In the diagram, a link represents the probability of a transition, and a node represents a sequence state.

For More Information: Microsoft Sequence Clustering Algorithm, Browse a Model Using the Microsoft Sequence Cluster Viewer

Refresh viewer content
Reload the mining model in the viewer.

Mining Model
Choose a mining model to view that is contained in the current mining structure. The mining model will open in its associated viewer.

Choose a viewer to use in exploring the selected mining model. You can use the custom viewer, or the Microsoft Generic Content Tree Viewer. You can also use plug-in viewers if available.

Zoom In
Zoom in to the diagram, to see the states better.

Zoom Out
Zoom out from the diagram, to get an overall view of the states in the cluster.

Copy Graph View
Copy the visible section of the diagram to the clipboard.

Copy Entire Graph
Copy the complete diagram to the clipboard.

Choose a cluster to display in the viewer. By default, Population (All) is selected, which means that states and transitions from the entire model are included in the graph. When you choose a particular cluster, only the states and transitions that are in that cluster are displayed.

Tip: You can rename clusters by using the Cluster Diagram tab. Just select a cluster, right-click, and select Rename. Renaming clusters with a more descriptive label makes it easier to compare clusters in the State Transitions tab.

Show Edge Labels
Select this option to display numbers on each edge in the graph that denote the probability of the transition.

Use the slider to control the number of states and transitions that are displayed in the chart. Lowering the slider shows only the states and transitions with the highest probability.

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