基本HTML版本
Genomics and Applied Biology
2014, Vol.5, No.3
http://gab.sophiapublisher.com
where
T
is the set of data items to be classified (the
test set),
tєT
,
t.c
is the class of the item
t
, and classify(
t
)
returns the classification of
t
by method. The best
supp
value is determined as the
supp
value for which the
test classification accuracy is the highest.
After conducting the classification of prostate cancer
data with AIS, an ANN structure was also trained and
tested for the same data. One-layer ANN architecture
was used and gradient descent learning rule was
utilized in the training. The optimum value of learning
rate parameter, the number of hidden nodes and the
momentum constant are also determined in the
experiments to give the highest test classification
accuracy. The results of ANN were compared with AIS.
Figure 1 The Flow chart of clonal based AIS system
For each
Ag
randomly generate an
initial population
Calculate affinities of
Ab
s in initial
population to presented
Ag
Select
Ab
s whose affinity is higher
than supp threshold for cloning and
mutation
Clon and mutate
selected
Ab
s
is max. İteration reached?
Select some good
Ab
s for
next iteration
add some randomly
generated
Ab
s for next
iteration
No
send highest affinity
Ab
to the memory
population is its affinity to current memory
Ab
s in the memory population is not higher
than supp threshold
Yes