Sequence Clustering Cluster Characteristics Tab (Mining Model Viewer)

  • Article

The Cluster Characteristics tab in the Microsoft Sequence Clustering Viewer provides a detailed list of the characteristics that define a sequence cluster. Those characteristics can include simple attribute-value pairs as well as transitions between states.

Use this view of a sequence clustering model to drill down into the cluster contents, and see the sequences that are representative of a cluster.

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

Options

  • 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.

  • 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.

  • Cluster
    Choose the cluster you want to view.

  • Characteristics for <Cluster>
    This table provides a list of the sequences that were assigned to the current cluster, ordered by probability. Remember that a sequence is basically one attribute-value pair, followed by one or more additional attribute-value pairs. The combination of sequences and their probabilities are the defining characteristics of each cluster.

    For example, in a sequence clustering model based on market basket analysis, one cluster might have as its top characteristic a customer choosing the sale item and then ending the transaction without purchasing anything more. In a sequence clustering model that seeks to analyze server failures, the primary characteristics of a cluster might be a series of high frequency error events.

    Value

    Description

    Variable

    This column indicates whether the characteristic is a value, or a transition.

    • If the characteristic is a value, the Variable column contains the attribute name.

    • If the characteristic represents a state transition, the Variable column contains the text “Transitions”.

    Values

    The value of this column depends on whether the characteristic is a simple attribute-value pair, or a state transition representing a common sequence of items or events.

    • If the characteristic is a value, the Value column contains the state.

    • If the characteristic represents a state transition, the Value column contains the description of the state transition.

    Probability

    This column displays a bar that indicates the relative probability that this characteristic (either a simple attribute-value pair, or some combination of states) are members of the current cluster.

    You can hover the mouse over the par to display the frequency value of the characteristic.

See Also

Reference

Mining Model Viewers (Data Mining Model Designer)

Concepts

Data Mining Algorithms (Analysis Services - Data Mining)

Data Mining Model Viewers