Parent Topic: <A href="http://www.pcigeomatics.com/cgi-bin/pcihlp/CLWORKS|Classify|Unsupervised+Algorithms|K-Means+&amp;+Fuzzy+K-Means">K-Means &amp; Fuzzy K-Means</a><hr>
<br><b>Max Sample Size</b><br>
Specifies the number of
samples to collect on which to perform the
the iterative clustering. This defaults to 262144 if not provided
by the user. If the indicated number is larger than the total
number of pixels in the image, then all the pixels in the image
will be used.<p>
The time to compute each iteration is proportional to the number
of samples used. This means that using a lot more than the default 
number of samples
can make the clustering process much slower. Also, all the samples
are stored in memory, meaning that a large NSAM value can lead to 
higher memory requirements. With 262144 samples and five bands 
of eight bit input data, the program would require approximately 1.3MB of
memory while with NSAM set to 2000000, it would take 10MB of memory.
<P>
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Parent Topic: <A href="http://www.pcigeomatics.com/cgi-bin/pcihlp/CLWORKS|Classify|Unsupervised+Algorithms|K-Means+&amp;+Fuzzy+K-Means">K-Means &amp; Fuzzy K-Means</a><br>
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