Information Technology Reference
In-Depth Information
Algorithm II
. Production of Mutated Clones
mutate
(
x
,
flag
){
For each binary feature element (i, j) in
x.f // note that x.f is basically a matrix
Do
Generate a random number,
r
in [0, 1]
If (
r
< MUTATION_RATE) Then
x.f
i,j
Å
toggle(
x.f
i,j
)
flag
Å
true
Endif
Done
}
Clone selection and update of immune memory:
Once the training criterion in
equation (3) is met for an antigen, the most stimulated (
w.r.t.
the current antigen un-
dergoing training)
b
-cell among the survived ones is selected as a candidate (let
b
candi-
date
denote this cell) to be inserted into immune memory. This process is outlined in
Algorithm III that is similar to one in [6]. This algorithm makes use of two parameters
AS
(average stimulation) and
is a user-defined
one, whereas
AS
is measured from the input training antigen set as the average stimu-
lation between all pairs of the mean values of the antigen classes.
α
(a scalar value). The parameter
α
Algorithm III
: Update of immune memory
CandStim
Å
stim
(
ag
i
,
b
candidate
)
MatchStim
Å
stim
(
ag
i
,
m
match
)
CellAff
Å
stim
(
m
match
,
b
candidate
)
If (
CandStim
>
MatchStim
)
IM
Å
IM
∪
b
candidate
// insertion into the immune memory
If (
CellAff
>
AS
)
IM
Å
IM
-
m
match
α
×
// memory replacement
Phase-II of the training algorithm:
Note that the training in Phase-I is a one-pass
method i.e. the system is trained only once on a training antigen. At the end of the
training phase, the immune memory i.e.
IM
0
={
m
1
,
m
2
, …,
m
m
} is produced. In the
present implementation, training involves a second phase namely Phase-II that
employs a refinement process. In this method recognition and training go hand in
hand to obtain a better immune memory from its initial version i.e.
IM
0
.
In this phase, recognition of the all the training antigens is done first using the
immune memory (
IM
i
,
i=
0, 1, …) obtained in the previous stage (say,
i
-th stage).
Classification strategy outlined next is used for recognition of antigens and the
recognition accuracy is noted. Next, antigens for which incorrect classification is
recorded act as a bootstrap samples that undergo further training involving clone
generation, selection and updating immune memory as outlined above in Phase-I of
the training. This results in an updated immune memory (
IM
i+1
), which is then used
for classification of all the training antigens. This newer version is retained if better
