Information Technology Reference
In-Depth Information
Table 2.
Linguistic values for input and output membership functions
Input
Output
VS
- Very Small
VS'
- Very Small
S
- Small
S'
- Small
MS
- Middle Small
MS'
- Middle Small
LS
- Little Small
LS'
- Little Small
LB
- Little Big
LB'
- Little Big
MB
- Middle Big
MB'
- Middle Big
B
- Big
B'
- Big
VB
- Very Big
These linguistic values were determined in such a manner that the allocated
resource number for ARBs which have stimulation values between 0 and 0.50 will
be less while for ARBs which have stimulation values between 0.50 and 1 will be
more.
4 The Experimental Results
In this section, we present the performance evaluation methods used to evaluate the
proposed method. Finally, we give the experimental results and discuss our observa-
tions from the obtained results.
4.1 Performance Evaluation
4.1.1 Classification Accuracy
In this study, the classification accuracies for the datasets are measured using Eq.(7)
[11]:
∑
=
T
assess(t
)
i
accuracy(T
)
=
i
1
,
t
∈
T
i
T
(
7
)
⎩
⎨
⎧
1,
if
classify(t
)
=
t.c
assess(t)
=
0,
otherwise
where
T
is the set of data items to be classified (the test set),
t
є
T
,
t.c
is the class of
item
t
, and classify(
t
) returns the classification of
t
by AIRS [11].
4.1.2 Sensitivity and Specificity Analysis
For sensitivity and specificity analysis, we use the following expressions.
