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11.3.2 Cluster Centroids Report


The Cluster Centroids Report provides a summary of the
patterns that are identified by the clustering procedure.
This report allows you to determine the characteristics of
the patterns that are identified.  Figure 11-2 illustrates a
sample Cluster Centroids Report.

CLUSTER CENTROIDS CLUSTER JOBMXNTA JOBTCBTM JOBNLR RADIUS NO ASSIGN PCT ------- -------- -------- -------- ------ --------- --- 1 0.0 0:00:05 3450.7 2.00 145 7 2 1.0 0:00:03 277.8 1.00 163 8 3 0.0 0:00:57 90.9 3.00 68 3 4 1.0 0:00:23 64.4 2.50 56 3 5 0.0 0:00:14 181.8 1.00 156 8 6 2.0 0:00:03 209.3 3.00 58 3 7 0.0 0:00:01 267.7 1.00 1172 59 8 0.0 0:00:07 8165.7 3.00 54 3 9 1.0 0:00:03 3950.7 2.50 20 1 10 0.0 0:00:11 12211.6 3.00 81 4 11 0.0 0:00:36 261.4 2.00 27 1


 Figure 11-2.  Cluster Assignment - Randomly Selected Sample Report

The Cluster Centroids Report lists the following fields:

CLUSTER:      The cluster number.  Cluster numbers are
              assigned sequentially to the patterns that are
              identified by the algorithm.  Note that the
              order in which the clusters are identified is
              not an indicator of merit.

A column is included in the report for each of the features
that are specified using the Workload Characterization screen
(see Section 11.5).  In the report shown in Figure 11-8, the
columns that are generated are JOBMXNTA, JOBTCBTM, and
JOBNLR.

JOBMXNTA:     The average number of tapes allocated by jobs
              assigned to the cluster.  Note that this
              variable is included in the CA MICS database
              only if the DVCT option is specified to the
              CA MICS Batch and Operations Analyzer.  In the
              distributed CA MICS system, this option is not
              activated.

JOBTCBTM:     The average CPU time consumed by jobs assigned
              to the cluster.

JOBNLR:       The average number of lines printed by jobs
              assigned to the cluster.

RADIUS:       The radius of the cluster in standard
              deviations.  Cluster radii vary from a minimum
              of 1.0 to a maximum of 3.0 standard deviations.

NO ASSIGN:    The number of resource vectors that were
              assigned to the cluster.  As a rule, the radius
              of a cluster is inversely proportional to the
              number of resource vectors assigned.  More
              simply stated, clusters that represent the
              highest percentages of the resource vectors are
              most likely to be those with the smallest
              radii.

PCT:          The percent of the resource vectors in the
              sample that are represented by the cluster.