[vtkusers] K-means values

[Thompson, David C]

Hi Sara,

> I'm using vtkKmeansStatistics to successfully cluster data points.
> However, I'm missing how you access the actual cluster mean values,
> instead of just their labels.  It looks like the order of the labels
> may not correspond to the values of the means, is this true?

I'm not clear on what you mean by "label". I've run the filter on data with 2 columns (named x & y) and with 2 sets of initial cluster center coordinates specified on the LEARN_PARAMETERS input: one for k=2 and one for k=3. I get this table:

+----------------+----------------+----------------+----------------+----------------+----------------+-----------------+
| Run ID         | k              | Iterations     | Error          | Cardinality    | x              | y               |
+----------------+----------------+----------------+----------------+----------------+----------------+-----------------+
| 0              | 2              | 3              | 1528.94        | 772            | 0.166201       | 0.12059         |
| 0              | 2              | 3              | 498.266        | 228            | 2.79467        | 2.99856         |
| 1              | 3              | 15             | 546.596        | 397            | -0.341883      | -0.486857       |
| 1              | 3              | 15             | 546.946        | 405            | 0.758854       | 0.855424        |
| 1              | 3              | 15             | 381.077        | 198            | 2.99941        | 3.14951         |
+----------------+----------------+----------------+----------------+----------------+----------------+-----------------+

as the first block of output 1 (i.e., GetOutputDataObject( 1 ).GetBlock( 0 ).Dump() will produce the above). The first 2 rows contain the cluster mean values corresponding to the run with k=2 and the final 3 rows have the same for the run with k=3. Because there are 2 coordinates (x & y) for each cluster center, there is no good way to order cluster centers by their means. Instead, their order matches the initial guesses at cluster centers specified on the LEARN_PARAMETERS input if it exists. Otherwise, the order is random because the initial guesses are produced randomly. Is this what you wanted to know?

    David