Performing K-means clustering

The K-means clustering tool is used to group the lines in a line chart into different groups (clusters) of similar lines.

About this task

The K-means clustering tool cannot be used unless you have created a suitable line chart to base the calculation on. For example, you cannot use multiple Y-axes scales or an X-axis which is both continuous and binned when performing a K-means clustering. See below for more information about how to configure the line chart. See also K-means clustering.

Tip: You can use a data function to do more generic K-means clustering operations.

Before you begin

Configuring and running the K-means clustering tool can only be done in the installed client.

Procedure

Create a line chart visualization by clicking Visualization types on the authoring bar and then, in the Visualization types flyout, selecting Line chart.
The K-means clustering tool uses the lines specified in a line chart to define the data for the calculation.
Make sure that all values that should be included in the calculation are selected on the Y-axis.
If more than one column is selected on the Y-axis, make sure that (Column Names) is selected on the X-axis.
(Column Names) is an option that treats the names of the columns selected on the Y-axis as separate categories.
Use Line by, Color by or Trellis by to split the lines by the values in at least one column, to create multiple lines.
See examples on how to split lines under Creating a line chart. If you want to create one line for each individual row, one of these options must be set to define a unique identifier for all rows. (Row Number) is a fictive column representing the row index of all rows and can be used for this purpose.
If desired, mark one or more lines to use as the master line against which the search will be performed.
On the menu bar, select Tools > K-means clustering.

Tip: You can also right-click the line chart, and select K-means clustering from the pop-up menu.
Make sure that the line chart you just created is selected under Line chart to work on.
Select whether to Create new result column or Update existing result column.
Update existing is only available when you have previously performed a K-means clustering during this analysis.
Select a Distance measure to use in the calculation.
For more information see Correlation or Euclidean distance.
Specify the Max number of clusters that you wish to create. The actual number of clusters might be smaller than the specified maximum.
Click OK.
A result column is created, specifying a cluster ID for each individual row (line). Note that the result column is based on a snapshot of the line chart from the moment of performing the calculation and it may become invalid when any additional filtering is applied.
Note: When opening an analysis file in which data has been saved linked to, any result columns generated by the clustering operation are dynamically re-evaluated, based on the new data.

Note: If the input line chart is trellised, the column or expression used to trellis by will be moved to the Line by setting upon running a K-means clustering. This is done in order to keep the original lines in the line chart after presenting the K-means result in trellis panels.