Parent Topic: <A href="http://www.pcigeomatics.com/cgi-bin/pcihlp/CLWORKS|Classify|Unsupervised+Algorithms">Unsupervised Algorithms</a><hr>
<H5>IsoData</H5>
This classifier performs unsupervised clustering using the ISODATA.
Up to 16 image channels can be analyzed and 255 clusters (classes) found 
using this program. The algorithm is controlled by the following parameters:
<P>
<br><b>Min Clusters</b><br>
Specifies the minimum number of clusters allowed. This parameter limits 
the number of clusters allowed during Lumping.  This parameter must be 
in the range from 1 to 255.  The default value is 16.
<P>
<br><b>Max Clusters</b><br>
Specifies the maximum number of clusters allowed. This parameter limits 
the total number of clusters allowed during splitting. This parameter must 
be in the range from 1 to 255. The default value is 16.
<P>
<br><b>Desired Clusters</b><br>
Specifies the number of clusters (classes) desired.  It should be noted 
that this is only an estimate. The final number of clusters may vary.
However, the user can limit the variation by setting the parameter's
Min Clusters and Max Clusters.  
This parameter must be in the range from 1 to 255. 
The default value is 16.
<P>
<br><b>Max Iterations</b><br>
Specifies the total number of iterations in calculating the 
cluster mean positions.
<P>
<br><b>Movement Threshold </b><br>
Specifies the movement threshold as a fraction of cluster means.
If the movement of all cluster means is less than Movement Threshold, the 
program has converged. The default is 0.01 or 1%.
<P>
<br><b>Min Threshold</b><br>
Specifies the minimum sample threshold.  The number of samples 
in a cluster domain is compared to Min Threshold in the following way:
 
When the number of samples in a cluster is less than the Min Threshold,
the cluster will be discarded and the total number of clusters
will be reduced by 1.  
 
For a cluster,
<P>
<UL>
<LI> if the standard deviation is greater than the Standard Deviation, AND
<LI> if the average distance of samples from the cluster center 
is greater than the overall average distance of the samples
from their respective cluster centers, AND 
<LI> if the total number of clusters is less than Max Clusters, AND
<LI> if the number of samples in the cluster is greater than 
2(Min Threshold+1), OR
<LI> if the number of clusters is less than or equal to Desired Clusters/2,
</UL>
then splitting of the cluster will occur.
<P>
<br><b>Standard Deviation</b><br>
If a cluster has a standard 
deviation greater than this parameter, splitting may occur.  
A value of 10.0 is reasonable.
<P>
<br><b>Lumping Threshold</b><br>
Specifies the lumping parameter which is used in the following way:<p>
If the distance between two cluster centers is less than this 
parameter, the total number of clusters is greater than Min 
Clusters, and the number of lumped pairs is less than Max Lump Pairs, 
then clusters will occur.
<P>
<br><b>Max Lump Pairs</b><br>
Specifies the maximum number of pairs of cluster centres which 
can be lumped during each iteration.
<P>
<br><b>Background</b><br>
Any pixel with this value will be ignored during the
classification and will be assigned to class 0 ( NULL class).
<P>
<hr>
Parent Topic: <A href="http://www.pcigeomatics.com/cgi-bin/pcihlp/CLWORKS|Classify|Unsupervised+Algorithms">Unsupervised Algorithms</a><br>
<a href="http://www.pcigeomatics.com/dev_corner/pcihlp_gateway.html">About PCI Help Gateway</a>