.NUMBER OF CLASSES: 40
[Enter number of classes required.]
.FACTOR NUMBERS: 1, 3, 4, 6
[Enter the factors to be included in the K-means clustering
algorithm.]
.FACTOR WEIGHT: 1.5
[Enter a weight for each factor selected. If the answer zero is
given at any point, all weights from the current factor onwards
are set to one. This question is asked as many times as the number
of factors specified, or is terminated by the answer zero.]
.FACTOR WEIGHT: 0.0
[This question is asked as many times as the number
of remaining factors, or is terminated by the answer zero.]
.FOR RANDOM SEEDS GIVE NON-ZERO STARTING NUMBER: 1457
[Initial partition of objects is random.
If the answer is zero, the partition is as follows:
1st object to first class,
2nd object to second class, ...,
k-th object to k-th class,
(k+1)-th object to first class, etc.
For non-zero answer, the number is used to initialize a truly
random assignment of objects.
The purpose is to try different initial partitions for a given
number of classes and choose the one with the best value of one
of the criteria.]
.SELECTION DOC FILE TEMPLATE (e.g.: SEL***): SEL***
[Enter template for selection document files which list
all the objects (usually images) belonging to the
same class. One file will be created for each class.]
.CLASS MEMBERSHIP DOC FILE: MAP001
[Enter the document file name where the class membership
for each object will be stored. File lists image number and
class number.]
NOTES