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5
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eo
p
le
g
r
ad
u
ated
o
n
tim
e
(
4
y
ea
r
s
)
with
a
p
er
ce
n
tag
e
o
f
1
.
9
0
%.
T
h
e
s
tu
d
y
p
er
io
d
was
4
.
5
-
5
y
ea
r
s
,
with
a
p
er
ce
n
tag
e
o
f
1
7
.
7
2
%
b
ein
g
4
0
p
eo
p
le.
T
h
e
s
tu
d
y
p
e
r
io
d
o
f
5
.
5
y
ea
r
s
-
6
y
ea
r
s
with
a
p
er
ce
n
tag
e
o
f
2
1
.
5
2
%
was
8
5
p
eo
p
le.
Fu
r
th
er
m
o
r
e,
th
e
d
o
m
in
an
t
s
tu
d
y
p
er
i
o
d
in
th
e
C
o
m
p
u
ter
Scien
ce
Dep
ar
tm
en
t
,
with
a
to
tal
o
f
1
1
0
p
e
o
p
le,
g
r
a
d
u
ated
with
a
s
tu
d
y
p
er
io
d
o
f
6
.
5
y
ea
r
s
-
7
y
ea
r
s
with
a
p
er
ce
n
tag
e
o
f
5
8
.
8
6
%.
T
h
is
s
h
o
ws
th
at
co
m
p
u
te
r
s
cien
ce
s
tu
d
en
ts
'
g
r
ad
u
atio
n
p
u
n
ctu
alit
y
is
s
till
v
er
y
lo
w,
with
a
p
er
ce
n
tag
e
o
f
1
.
9
0
%.
T
h
is
s
tu
d
en
t
g
r
ad
u
atio
n
p
r
e
d
ictio
n
s
y
s
tem
r
eq
u
ir
es
ex
is
t
in
g
in
f
o
r
m
atio
n
t
o
d
eter
m
in
e
wh
eth
er
a
s
tu
d
e
n
t
ca
n
g
r
ad
u
ate
o
n
tim
e
[
7
]
.
Su
p
p
o
s
e
s
tu
d
en
t
g
r
ad
u
atio
n
ca
n
b
e
k
n
o
wn
ea
r
l
y
o
n
;
i
n
th
at
ca
s
e,
th
e
ac
a
d
em
ic
p
a
r
t
y
ca
n
im
p
lem
en
t
a
p
o
licy
to
m
in
im
ize
th
e
n
u
m
b
er
o
f
s
tu
d
en
ts
wh
o
d
o
n
o
t
g
r
ad
u
ate
o
n
tim
e
ac
co
r
d
in
g
to
th
eir
s
tu
d
y
p
er
i
o
d
.
B
ased
o
n
th
ese
d
ata,
co
m
p
letin
g
s
tu
d
ies
o
n
tim
e
is
im
p
o
r
tan
t
f
o
r
b
o
th
s
tu
d
e
n
ts
an
d
th
e
C
o
m
p
u
ter
Scien
ce
Dep
ar
tm
en
t
.
Acc
r
e
d
itatio
n
Dep
ar
tm
en
t
is
an
ass
es
s
m
en
t o
f
a
d
ep
ar
tm
en
t'
s
e
lig
ib
ilit
y
.
Alu
m
n
i d
ata,
ac
tiv
e
s
tu
d
en
ts
,
an
d
o
u
ts
tan
d
in
g
s
tu
d
en
ts
ar
e
am
o
n
g
th
e
ass
es
s
m
en
ts
in
th
e
ac
cr
ed
ita
tio
n
o
f
th
e
c
o
m
p
u
te
r
s
cien
c
e
d
ep
ar
tm
e
n
t.
W
ith
th
e
p
r
e
d
ictio
n
o
f
s
tu
d
en
t
g
r
ad
u
atio
n
,
it
is
h
o
p
ed
th
at
it
ca
n
b
e
a
r
ef
er
en
ce
f
o
r
ac
ad
e
m
ics
in
s
ett
in
g
s
tr
ateg
ies
f
o
r
t
h
eir
s
tu
d
en
ts
s
o
th
at
th
ey
ca
n
c
o
m
p
lete
th
eir
s
tu
d
ie
s
o
n
tim
e
[
8
]
.
T
h
e
r
ig
h
t
s
tr
ateg
y
f
o
r
s
tu
d
e
n
ts
s
till
s
tu
d
y
in
g
to
co
m
p
lete
th
e
ir
s
tu
d
ies
o
n
tim
e
is
to
u
s
e
th
e
r
o
u
g
h
s
et
m
eth
o
d
.
T
h
e
r
o
u
g
h
s
et
m
eth
o
d
is
a
ca
lcu
latio
n
m
eth
o
d
s
u
itab
le
f
o
r
d
eter
m
in
in
g
th
e
lev
el
o
f
s
tu
d
en
t
g
r
ad
u
atio
n
[
9
]
.
T
h
r
o
u
g
h
th
e
r
o
u
g
h
s
et
m
eth
o
d
,
it
ca
n
b
e
u
s
ed
to
p
r
o
d
u
ce
o
u
tp
u
t
in
th
e
f
o
r
m
o
f
s
tu
d
e
n
t
g
r
ad
u
atio
n
p
r
ed
ictio
n
s
.
T
h
e
p
u
r
p
o
s
e
o
f
im
p
lem
e
n
tin
g
th
is
m
eth
o
d
is
to
h
elp
ac
ad
em
ics
k
n
o
w
th
e
p
o
s
s
ib
ilit
y
o
f
s
tu
d
en
t g
r
ad
u
atio
n
b
ased
o
n
s
tu
d
en
t d
ata
th
at
h
as b
ee
n
s
t
o
r
ed
.
T
h
e
b
e
n
ef
its
o
b
tain
e
d
ar
e
th
at
th
e
p
o
s
s
ib
ilit
y
o
f
s
tu
d
en
t
g
r
ad
u
atio
n
ca
n
b
e
d
eter
m
in
ed
ea
r
ly
o
n
b
ased
o
n
th
e
k
n
o
wled
g
e
o
b
tain
e
d
th
r
o
u
g
h
th
e
r
o
u
g
h
s
et
m
eth
o
d
.
Af
ter
o
b
tain
in
g
k
n
o
w
led
g
e
f
r
o
m
th
e
r
o
u
g
h
s
et
m
eth
o
d
,
th
e
s
im
ilar
ity
p
r
o
ce
s
s
is
co
n
tin
u
ed
to
p
r
ed
ict
s
tu
d
en
t
g
r
ad
u
atio
n
.
I
n
th
is
s
tu
d
y
,
r
esear
ch
e
r
s
u
s
ed
co
s
in
e
s
i
m
ilar
ity
to
ca
lcu
late
th
e
h
i
g
h
e
s
t
s
im
ilar
ity
v
alu
e
b
ased
o
n
k
n
o
wled
g
e.
T
h
ese
r
e
s
u
lts
p
r
o
d
u
ce
a
s
o
lu
tio
n
o
r
p
r
e
d
ictio
n
o
f
s
tu
d
en
t g
r
a
d
u
atio
n
[
1
0
]
.
Pre
v
i
o
u
s
r
es
ea
r
c
h
als
o
r
e
v
i
ew
ed
t
h
e
p
r
e
d
i
cti
o
n
o
f
s
t
u
d
e
n
t
g
r
a
d
u
ati
o
n
u
s
i
n
g
t
h
e
k
-
n
ea
r
es
t
n
ei
g
h
b
o
r
(k
-
N
N)
a
lg
o
r
it
h
m
,
wi
th
t
h
e
p
r
o
b
le
m
b
ei
n
g
t
h
e
p
e
r
c
e
n
ta
g
e
o
f
u
p
s
a
n
d
d
o
w
n
s
o
f
s
tu
d
e
n
t'
s
ab
i
lit
y
t
o
co
m
p
l
ete
th
e
ir
s
t
u
d
ies
o
n
t
im
e
as
o
n
e
o
f
th
e
e
le
m
e
n
ts
o
f
u
n
i
v
e
r
s
it
y
ac
cr
ed
itat
io
n
ass
ess
m
e
n
t
.
T
h
e
r
e
s
u
lt
is
t
h
a
t
t
h
e
le
v
el
o
f
ac
c
u
r
ac
y
o
f
test
in
g
th
e
s
t
u
d
en
t
g
r
a
d
u
a
ti
o
n
m
o
d
el
u
s
i
n
g
t
h
e
k
-
NN
al
g
o
r
it
h
m
u
s
i
n
g
t
h
e
at
tr
i
b
u
tes
o
f
g
e
n
d
e
r
,
m
a
r
it
al
s
t
at
u
s
,
e
m
p
lo
y
m
e
n
t
s
ta
tu
s
,
a
n
d
i
n
d
e
ks
p
r
est
a
s
i
s
em
est
er
(
I
PS
)
I
-
I
V
is
i
n
f
l
u
e
n
c
e
d
b
y
th
e
n
u
m
b
e
r
o
f
d
ata
clu
s
te
r
i
n
g
.
T
h
e
h
i
g
h
est
ac
cu
r
ac
y
a
n
d
a
r
e
a
u
n
d
er
th
e
c
u
r
v
e
(
AUC
)
v
al
u
e
is
b
y
cl
u
s
t
e
r
i
n
g
t
h
e
5
th
d
a
ta
.
T
h
e
ac
c
u
r
a
cy
v
a
lu
e
is
8
5
.
1
5
%
an
d
t
h
e
A
UC
v
al
u
e
is
0
.
8
8
8
[
1
1
]
.
T
h
e
lat
est
r
ese
a
r
c
h
b
y
Pe
li
m
a
e
t
a
l
.
[
1
2
]
e
n
ti
tle
d
“Pr
ed
ict
in
g
t
h
e
l
e
v
el
o
f
s
tu
d
en
t
g
r
a
d
u
ati
o
n
o
n
t
im
e
u
s
i
n
g
n
ai
v
e
B
a
y
es
”.
T
h
e
p
r
o
b
le
m
is
t
h
a
t
i
t
was
f
o
u
n
d
th
at
th
e
n
u
m
b
er
o
f
n
ew
s
t
u
d
e
n
ts
is
g
r
ea
te
r
t
h
a
n
t
h
e
n
u
m
b
e
r
o
f
s
t
u
d
e
n
ts
w
h
o
g
r
a
d
u
a
te
d
a
n
d
h
a
v
e
n
o
t
b
ee
n
ab
le
t
o
p
r
o
d
u
c
e
k
n
o
w
le
d
g
e
ab
o
u
t th
is
co
n
d
iti
o
n
.
T
h
e
at
tr
ib
u
t
es u
s
e
d
in
th
is
s
t
u
d
y
a
r
e
g
e
n
d
e
r
,
t
y
p
e
o
f
s
e
lec
ti
o
n
,
f
a
th
e
r
'
s
in
c
o
m
e
,
m
o
t
h
e
r
'
s
e
d
u
ca
ti
o
n
,
I
PS
I
-
I
V,
a
n
d
s
em
este
r
c
r
e
d
its
I
-
I
V.
T
h
e
r
es
u
lt
is
th
at
t
h
e
a
cc
u
r
ac
y
o
f
t
h
e
d
a
ta
test
i
n
g
o
b
t
ai
n
e
d
i
n
t
h
is
s
tu
d
y
i
s
8
0
.
7
2
%
o
f
t
h
e
1
1
6
2
d
ata
u
s
e
d
f
o
r
t
r
ai
n
i
n
g
d
at
a
a
n
d
5
8
7
d
at
a
f
o
r
test
in
g
.
B
ase
d
o
n
t
h
e
p
r
o
b
l
em
s
an
d
p
r
ev
io
u
s
r
es
ea
r
c
h
,
t
h
is
s
t
u
d
y
w
as
c
o
n
d
u
cte
d
t
o
m
e
asu
r
e
an
d
p
r
ed
ict
t
h
e
g
r
a
d
u
ati
o
n
r
ate
o
f
co
m
p
u
te
r
s
cie
n
ce
s
t
u
d
en
ts
at
Un
i
v
e
r
s
i
ty
X
,
wh
ic
h
lat
er
t
h
e
d
at
a
a
n
d
r
e
co
m
m
e
n
d
ati
o
n
s
p
r
o
d
u
ce
d
c
an
b
e
u
s
e
d
as
a
r
e
f
e
r
en
ce
i
n
ta
k
i
n
g
s
t
r
at
e
g
ic
s
tep
s
f
o
r
t
h
e
s
tu
d
y
p
r
o
g
r
am
.
T
h
is
s
t
u
d
y
u
s
es
a
c
o
s
in
e
s
i
m
il
ar
ity
ap
p
r
o
ac
h
wi
th
a
r
o
u
g
h
s
et
t
h
at
is
d
if
f
e
r
e
n
t
f
r
o
m
s
e
v
e
r
a
l
p
r
e
v
i
o
u
s
s
t
u
d
ies
t
h
a
t
u
s
e
a
l
o
t
o
f
k
-
N
N
an
d
n
ai
v
e
B
a
y
es.
2.
M
E
T
H
O
D
2
.
1
.
D
a
t
a
Data
f
r
o
m
th
e
2
0
1
9
-
2
0
2
4
b
a
tch
,
as
m
an
y
as
2
6
0
d
atasets
,
wer
e
u
s
ed
in
th
is
s
tu
d
y
.
O
f
th
e
2
6
0
d
atasets
u
s
ed
,
7
0
%
o
f
th
e
d
a
ta
is
tr
ain
in
g
d
ata,
an
d
3
0
%
o
f
th
e
d
ata
is
test
d
ata.
T
h
e
attr
ib
u
tes
u
s
ed
ar
e
g
en
d
er
,
Gr
ad
e
p
o
in
ts
in
s
em
ester
2
,
a
n
d
GPA
in
s
em
ester
4
.
T
h
e
d
ata
o
b
tain
e
d
is
g
iv
e
n
co
d
es.
T
h
is
is
u
s
ef
u
l
f
o
r
s
im
p
lify
in
g
th
e
ca
lcu
latio
n
s
tag
e.
T
h
e
f
o
llo
win
g
ar
e
th
e
c
o
d
es
an
d
d
escr
ip
tio
n
s
u
s
ed
f
o
r
g
r
ad
e
p
o
in
ts
(
GP)
an
d
GPA
d
ef
i
n
ed
b
y
t
h
e
s
y
m
b
o
l
(
,
,
,
,
)
.
T
h
e
s
y
m
b
o
l
is
id
en
tif
ied
th
e
r
a
n
g
e
o
f
GPA
th
at
s
h
ar
ed
b
y
ex
p
er
t
(
d
ea
n
o
f
f
ac
u
lty
co
m
p
u
ter
s
cien
ce
)
.
T
h
e
d
etails
ar
e
:
=
3
,
0
0
-
4
,
0
0
;
=
2
,
5
0
-
2
,
9
9
;
=
2
,
0
0
-
2
,
4
9
;
=
1
,
5
1
-
1
,
9
9
;
=
≤
1
,
5
0
.
An
d
f
o
r
g
e
n
d
er
is
s
ep
ar
ate
to
g
en
d
e
r
it
is
f
o
r
wo
m
an
an
d
f
o
r
m
a
n
.
Fo
r
r
ec
o
m
m
en
d
atio
n
d
iv
id
e
b
y
4
ca
teg
o
r
ies
:
=
g
r
ad
u
ated
≤
4
,
0
0
y
ea
r
s
;
=
g
r
ad
u
ated
4
,
5
–
5
,
0
0
y
ea
r
s
;
=
g
r
ad
u
ated
5
,
5
–
6
,
0
0
y
ea
r
s
;
an
d
=
g
r
ad
u
ated
6
,
5
–
7
,
0
0
y
ea
r
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
C
o
mb
in
a
tio
n
o
f ro
u
g
h
s
et
a
n
d
co
s
in
e
s
imila
r
ity
a
p
p
r
o
a
ch
es in
…
(
R
a
tn
a
Yu
lika
Go
)
6003
2
.
2
.
Ca
s
e
-
b
a
s
ed
r
e
a
s
o
n
in
g
I
n
g
en
e
r
al,
ca
s
e
-
b
ased
r
ea
s
o
n
i
n
g
ca
s
e
-
b
ased
r
ea
s
o
n
i
n
g
(
C
B
R
)
is
a
co
n
ce
p
t
o
f
r
ea
s
o
n
i
n
g
i
n
p
r
o
b
lem
-
s
o
lv
in
g
th
r
o
u
g
h
ca
s
e
h
an
d
lin
g
r
ec
o
r
d
s
th
at
a
n
ex
p
e
r
t
h
as
ca
r
r
ied
o
u
t.
C
ase
-
b
ased
r
ea
s
o
n
i
n
g
h
as
f
o
u
r
s
tag
es,
wh
ich
in
clu
d
e
[
1
3
]
:
a.
R
etr
iev
e:
Gettin
g
/r
etr
iev
in
g
th
e
m
o
s
t similar
/r
elev
an
t c
ases
to
th
e
n
ew
ca
s
e.
b.
R
eu
s
e
:
Mo
d
elin
g
/r
eu
s
in
g
k
n
o
wled
g
e
an
d
in
f
o
r
m
atio
n
f
r
o
m
o
ld
ca
s
es b
ased
o
n
th
e
m
o
s
t r
e
lev
an
t similar
ity
weig
h
ts
in
to
n
ew
ca
s
es.
c.
R
ev
is
e:
R
ev
iew
in
g
th
e
p
r
o
p
o
s
ed
s
o
lu
tio
n
an
d
th
en
test
in
g
it o
n
r
ea
l c
ases
(
s
im
u
latio
n
)
.
d.
R
etain
:
I
n
teg
r
atin
g
/s
av
in
g
n
e
w
ca
s
es
th
at
h
av
e
s
u
cc
es
s
f
u
lly
o
b
tain
ed
s
o
lu
tio
n
s
s
o
th
at
th
e
y
ca
n
b
e
u
s
ed
b
y
s
u
b
s
eq
u
en
t c
ases
s
im
ilar
to
th
e
ca
s
e.
2
.
3
.
P
re
-
pro
ce
s
s
ing
I
n
th
is
s
tu
d
y
,
p
r
e
-
p
r
o
ce
s
s
in
g
is
ca
r
r
ied
o
u
t
u
s
in
g
th
e
o
u
tlier
f
u
n
ctio
n
b
ef
o
r
e
th
e
d
ata
is
p
r
o
ce
s
s
ed
.
B
ased
o
n
th
e
d
ata
o
b
tain
e
d
,
th
e
d
ata
is
class
if
ied
as
an
o
u
tli
er
[
1
4
]
.
T
h
is
m
ea
n
s
th
at
th
e
o
b
s
er
v
atio
n
d
ata
th
at
ap
p
ea
r
s
h
as
ex
tr
em
e
v
alu
es
o
r
v
alu
es
th
at
a
r
e
f
a
r
f
r
o
m
m
o
s
t
o
f
th
e
o
t
h
er
v
alu
es
in
its
g
r
o
u
p
.
So
,
th
e
o
u
tlie
r
d
ata
n
ee
d
s
to
b
e
clea
n
ed
in
o
r
d
er
t
o
g
et
g
o
o
d
r
esu
lts
.
As
m
an
y
as
7
0
%
o
f
th
e
tr
ain
in
g
d
ata
o
r
1
8
2
d
atasets
u
s
in
g
th
e
o
u
tlier
f
u
n
ctio
n
p
r
o
d
u
ce
d
1
8
1
clea
n
d
atasets
.
T
h
e
r
esu
lts
o
f
t
h
e
o
u
tlier
f
u
n
ctio
n
ar
e
th
e
n
ca
lcu
lated
u
s
in
g
th
e
in
d
e
x
in
g
m
eth
o
d
,
n
a
m
ely
r
o
u
g
h
s
et.
2
.
4
.
Ro
ug
h
s
e
t
A
r
o
u
g
h
s
et
is
a
m
ath
em
atica
l
tech
n
iq
u
e
d
e
v
elo
p
ed
b
y
Pawlak
in
1
9
9
1
.
T
h
e
s
tep
s
in
d
eter
m
in
in
g
th
e
r
ed
u
ctio
n
i
n
eq
u
i
v
alen
ce
class
es a
r
e
as
[
1
5
]
:
a.
Data
r
ep
r
esen
tatio
n
:
R
o
u
g
h
s
et
is
r
ep
r
esen
ted
b
y
two
elem
en
ts
,
n
am
ely
in
f
o
r
m
a
tio
n
s
y
s
tem
s
(
I
S)
an
d
d
ec
is
io
n
s
y
s
tem
s
(
DS)
.
An
is
d
ef
in
ed
as
a
p
air
=
{
,
}
,
wh
er
e
=
{
₁
,
₂
,
.
.
.
,
ₘ
}
r
ep
r
esen
ts
a
s
et
o
f
ca
s
es,
an
d
=
{
₁
,
₂
,
.
.
.
,
ₙ
}
r
ep
r
esen
ts
a
s
et
o
f
attr
i
b
u
tes.
T
h
e
in
f
o
r
m
atio
n
s
y
s
tem
in
t
h
e
co
n
tex
t
o
f
th
e
s
y
s
tem
ca
n
b
e
illu
s
tr
ated
in
a
T
ab
le
1.
T
ab
le
1
.
I
n
f
o
r
m
atio
n
s
y
s
t
e
m
s
G
P
A
G
e
n
d
e
r
G
P
R
e
c
o
m
m
e
n
d
a
t
i
o
n
q
q
q
b
q
p
q
b
r
q
q
b
q
q
r
b
q
q
q
b
T
h
e
d
ata
is
an
e
x
am
p
le
o
f
5
ca
s
es,
ev
alu
ated
u
s
in
g
t
h
e
p
ar
am
eter
s
GPA,
g
en
d
er
,
a
n
d
I
P.
I
n
an
in
f
o
r
m
atio
n
s
y
s
tem
,
ea
c
h
r
o
w
r
ep
r
esen
ts
a
n
o
b
ject,
wh
ile
e
ac
h
co
lu
m
n
r
ep
r
esen
ts
a
n
attr
ib
u
te,
co
n
s
is
tin
g
o
f
o
b
jects:
=
{
₁
,
₂
,
.
.
.
,
ₘ
}
: c
ases
1
,
2
,
3
,
.
.
.
,
2
0
=
{
₁
,
₂
,
.
.
.
,
ₙ
}
: G
PA,
g
en
d
er
,
I
P
I
n
m
a
n
y
a
p
p
licatio
n
s
,
a
n
o
u
t
co
m
e
o
r
class
if
icatio
n
d
ec
is
io
n
is
k
n
o
wn
,
wh
ich
is
r
ep
r
ese
n
ted
b
y
a
d
ec
is
io
n
attr
ib
u
te
,
=
{
₁
,
₂
,
.
.
.
,
ₚ
}
.
T
h
er
ef
o
r
e
,
th
e
in
f
o
r
m
atio
n
s
y
s
tem
b
ec
o
m
es:
=
(
,
{
,
}
)
.
E
ac
h
o
b
ject
in
th
e
s
y
s
tem
i
s
d
escr
ib
ed
b
y
v
alu
es
o
f
th
ese
attr
ib
u
tes,
p
r
o
v
id
in
g
a
s
tr
u
ctu
r
ed
way
to
ca
p
tu
r
e
i
n
f
o
r
m
atio
n
.
W
h
en
a
s
p
ec
ial
attr
ib
u
te
r
ep
r
esen
tin
g
d
ec
is
io
n
s
o
r
o
u
tco
m
es
is
ad
d
ed
,
th
e
s
y
s
tem
b
ec
o
m
es
a
d
ec
is
io
n
s
y
s
tem
,
w
h
ich
f
ac
ilit
ates
class
if
icatio
n
an
d
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
es.
Dec
is
io
n
s
y
s
tem
s
lin
k
th
e
co
n
d
itio
n
attr
ib
u
tes
with
d
ec
is
io
n
attr
ib
u
tes,
e
n
ab
lin
g
th
e
an
aly
s
is
o
f
h
o
w
d
if
f
er
en
t
attr
ib
u
te
co
m
b
in
atio
n
s
in
f
lu
en
ce
s
p
ec
if
i
c
o
u
tco
m
es.
T
h
is
s
tr
u
ctu
r
e
is
f
u
n
d
am
e
n
tal
in
r
o
u
g
h
s
et
th
eo
r
y
,
wh
er
e
it h
elp
s
in
id
en
tify
in
g
p
atter
n
s
,
d
e
p
en
d
e
n
cies,
an
d
r
u
les with
in
d
ata
f
o
r
k
n
o
wled
g
e
d
is
co
v
er
y
an
d
r
ea
s
o
n
in
g
.
b.
Po
s
itiv
e
r
e
g
i
o
n
I
n
r
o
u
g
h
s
et
th
eo
r
y
,
th
e
p
o
s
itiv
e
r
eg
io
n
r
e
p
r
esen
ts
th
e
s
et
o
f
o
b
jects
in
t
h
e
u
n
iv
er
s
e
t
h
at
ca
n
b
e
ce
r
tain
ly
class
if
ied
in
to
s
p
ec
if
ic
d
ec
is
io
n
class
es
b
ased
o
n
th
e
g
iv
en
co
n
d
itio
n
attr
ib
u
tes.
I
t
is
f
o
r
m
ed
b
y
co
m
b
in
in
g
all
th
e
lo
wer
a
p
p
r
o
x
im
atio
n
s
o
f
th
e
d
ec
is
io
n
attr
i
b
u
te
p
ar
titi
o
n
s
.
T
h
e
l
o
wer
ap
p
r
o
x
im
atio
n
co
n
s
is
ts
o
f
o
b
jects
wh
o
s
e
eq
u
i
v
alen
ce
class
es,
d
ef
in
ed
b
y
co
n
d
itio
n
attr
ib
u
tes,
ar
e
en
tire
l
y
in
clu
d
e
d
with
in
a
p
ar
ticu
la
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
6
,
Decem
b
e
r
20
25
:
6
0
0
1
-
6
0
1
1
6004
d
ec
is
io
n
class
.
B
y
u
n
itin
g
th
ese
lo
wer
ap
p
r
o
x
im
atio
n
s
,
th
e
p
o
s
itiv
e
r
eg
io
n
h
elp
s
id
en
tif
y
wh
ich
d
ata
p
o
in
ts
ca
n
b
e
d
ef
in
itiv
el
y
ca
teg
o
r
ize
d
with
o
u
t
am
b
ig
u
ity
.
T
h
is
co
n
ce
p
t
is
ess
en
tial
f
o
r
ev
alu
atin
g
th
e
class
if
icatio
n
p
o
wer
o
f
th
e
attr
ib
u
tes u
s
ed
i
n
a
d
ec
is
io
n
s
y
s
tem
.
c.
E
q
u
iv
alen
ce
c
l
a
s
s
I
n
th
e
p
o
s
itiv
e
r
eg
io
n
,
ca
s
es
w
ith
eq
u
iv
ale
n
t
attr
ib
u
te
v
alu
es
b
ased
o
n
th
e
d
ec
is
io
n
attr
i
b
u
t
e
.
ar
e
g
r
o
u
p
ed
in
to
e
q
u
iv
alen
c
e
clas
s
es.
T
h
ese
class
es
co
n
s
is
t
o
f
o
b
jects
(
ca
s
es)
th
at
s
h
a
r
e
id
e
n
tical
v
alu
es
f
o
r
th
e
co
n
d
itio
n
attr
ib
u
tes
an
d
ar
e
f
u
lly
co
n
tain
ed
with
in
a
s
in
g
l
e
d
ec
is
io
n
class
.
T
h
e
u
n
io
n
o
f
th
ese
eq
u
iv
alen
ce
class
es
th
at
m
ee
t
th
is
cr
iter
io
n
f
o
r
m
s
th
e
p
o
s
itiv
e
r
eg
io
n
.
T
h
is
ap
p
r
o
ac
h
e
n
s
u
r
es
th
at
o
n
l
y
th
o
s
e
ca
s
es
wh
ich
ca
n
b
e
ce
r
tain
ly
class
if
ied
(
with
o
u
t
am
b
ig
u
ity
)
ar
e
in
clu
d
e
d
in
th
e
d
ec
is
io
n
p
r
o
ce
s
s
.
T
h
e
eq
u
iv
alen
ce
class
g
r
o
u
p
s
th
e
s
am
e
o
b
jects f
o
r
attr
ib
u
te
(
,
)
.
T
h
e
eq
u
i
v
alen
ce
class
tab
le
is
s
h
o
wn
in
T
ab
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m
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q
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i
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C
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m
p
ar
e
ea
ch
class
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th
er
e
is
a
d
if
f
er
en
ce
in
an
y
class
attr
ib
u
te,
r
ec
o
r
d
it
in
th
e
d
is
ce
r
n
ib
ilit
y
m
atr
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f
all
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tes
ar
e
th
e
s
am
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m
ar
k
it
with
a
cr
o
s
s
(
Nu
ll).
T
h
e
attr
ib
u
tes
ar
e
r
ep
r
esen
te
d
as
f
o
llo
ws:
GPA,
g
en
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er
,
an
d
I
P.
T
o
ev
al
u
ate
th
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d
iag
n
o
s
tic
p
er
f
o
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m
a
n
ce
o
f
an
alg
o
r
ith
m
,
th
e
b
est
alg
o
r
ith
m
is
o
n
e
th
at
n
o
t o
n
l
y
d
em
o
n
s
tr
ates stro
n
g
p
e
r
f
o
r
m
an
ce
b
u
t a
ls
o
h
as th
e
p
o
ten
tial to
ac
cu
r
ately
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iag
n
o
s
e
d
ata.
d.
Dis
ce
r
n
ib
ilit
y
m
a
t
r
i
x
At
th
e
d
is
ce
r
n
ib
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atr
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s
tag
e,
th
e
d
ata
in
th
e
f
o
r
m
o
f
a
tab
le
is
p
r
o
ce
s
s
ed
b
y
co
m
p
ar
in
g
an
d
co
n
s
id
er
in
g
o
n
ly
th
e
c
o
n
d
itio
n
v
ar
iab
les.
Fr
o
m
th
is
s
tag
e,
th
e
p
r
o
ce
s
s
o
f
s
elec
tin
g
m
in
im
al
v
ar
iab
les
f
r
o
m
a
s
et
o
f
co
n
d
itio
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v
ar
ia
b
les
is
ca
r
r
ied
o
u
t
u
s
in
g
th
e
p
r
im
e
im
p
lican
t
B
o
o
lean
f
u
n
ctio
n
.
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p
r
i
m
e
i
m
p
l
i
c
a
n
t
i
n
a
B
o
o
l
e
a
n
f
u
n
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ti
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o
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f
1
(
t
r
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f
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t
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ic
c
i
r
c
u
it
r
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p
r
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s
e
n
ta
t
i
o
n
[
1
6
]
.
T
h
e
r
esu
lt
o
f
k
n
o
wled
g
e
is
th
e
in
d
ex
in
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p
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s
s
u
s
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f
o
r
th
e
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o
s
in
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s
im
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ity
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r
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s
s
.
Af
ter
th
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in
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ex
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r
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en
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in
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atab
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ly
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in
d
ex
as
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ase
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test
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th
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v
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lcu
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d
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(
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wh
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m
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[
1
7
]
.
T
h
e
f
o
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m
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a
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[
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ex
p
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t
h
at
th
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g
r
ea
ter
th
e
r
esu
lt o
f
th
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s
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f
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aller
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lt
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th
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m
o
r
e
d
i
f
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er
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th
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n
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f
u
n
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at
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v
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0
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.
.
1
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tire
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if
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[
1
9
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2
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5
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As
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2
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6
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e
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s
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d
en
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ad
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.
T
h
e
s
y
s
tem
h
as
4
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r
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s
s
s
tag
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s
:
r
etr
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r
eu
s
e,
r
ev
is
e,
an
d
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etain
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T
h
e
way
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s
y
s
tem
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r
k
s
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g
en
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is
g
u
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y
th
e
k
n
o
wle
d
g
e
b
ase
o
wn
ed
b
y
th
e
s
y
s
tem
,
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is
s
o
u
r
ce
d
f
r
o
m
alu
m
d
ata,
wh
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is
th
en
ca
lcu
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f
o
r
its
s
im
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ity
le
v
el
with
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ew
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s
es
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ter
ed
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e
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s
er
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ased
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th
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s
e,
th
e
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ad
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wh
ic
h
ar
e
e
x
p
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ted
to
h
elp
t
h
e
s
tu
d
y
p
r
o
g
r
a
m
o
r
s
y
s
tem
u
s
er
s
p
r
ed
ict
s
tu
d
e
n
t
g
r
ad
u
atio
n
.
2
.
7
.
Sy
s
t
e
m
t
esting
m
et
ho
d
Sy
s
tem
test
in
g
u
tili
ze
d
th
e
k
-
f
o
ld
cr
o
s
s
v
alid
atio
n
m
eth
o
d
,
wh
er
e
th
e
d
ataset
was
r
an
d
o
m
ly
d
iv
id
e
d
in
to
K
p
ar
titi
o
n
s
(
f
o
ld
s
)
.
Su
b
s
eq
u
en
tly
,
K
iter
atio
n
s
o
f
ex
p
er
im
en
ts
wer
e
co
n
d
u
cted
.
I
n
ea
ch
iter
atio
n
,
o
n
e
d
is
tin
ct
f
o
ld
was u
s
ed
as th
e
te
s
tin
g
s
et,
wh
ile
th
e
r
em
ain
in
g
K
–
1
f
o
ld
s
wer
e
u
s
ed
f
o
r
tr
ain
in
g
.
T
h
is
ap
p
r
o
ac
h
en
s
u
r
es
th
at
e
v
er
y
d
ata
p
o
i
n
t
is
u
s
ed
f
o
r
b
o
th
tr
ain
in
g
an
d
test
in
g
,
th
er
eb
y
e
n
h
an
ci
n
g
th
e
r
o
b
u
s
tn
ess
an
d
g
en
er
aliza
b
ilit
y
o
f
th
e
m
o
d
el
e
v
alu
atio
n
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
P
r
e
p
r
o
c
es
s
i
n
g
B
ef
o
r
e
th
e
d
ata
is
p
r
o
ce
s
s
ed
,
p
r
ep
r
o
ce
s
s
in
g
is
ca
r
r
ied
o
u
t
b
y
p
er
f
o
r
m
in
g
o
u
tlier
s
.
T
o
f
in
d
o
u
t
th
e
tr
u
th
o
f
th
e
s
y
s
tem
'
s
ac
cu
r
ac
y
r
esu
lts
,
r
esear
ch
er
s
u
s
e
th
e
o
u
tlier
f
u
n
ctio
n
to
f
in
d
o
u
t
wh
at
p
er
ce
n
tag
e
o
f
d
ata
is
b
iased
.
B
ec
au
s
e
th
e
m
o
r
e
o
u
tlier
d
ata
th
er
e
ar
e,
th
e
les
s
b
iased
d
ata
t
h
er
e
will
b
e,
a
n
d
v
ice
v
er
s
a.
T
h
e
r
esu
lts
o
f
th
e
o
u
tlier
s
o
b
tain
ed
1
d
ata
th
at
was
s
ig
n
if
ican
t
en
o
u
g
h
s
o
th
at
th
e
d
ata
was
clea
n
ed
o
r
d
elete
d
.
Of
th
e
182
-
tr
ai
n
in
g
d
ata
a
f
ter
u
s
in
g
o
u
tlier
s
,
o
n
l
y
1
was
lo
s
t,
s
o
th
e
clea
n
d
ata
o
b
tai
n
ed
was
1
8
1
.
T
h
e
r
esu
lts
o
f
th
is
s
tu
d
y
o
b
tain
ed
in
d
ex
i
n
g
o
f
1
0
r
u
les/
k
n
o
wled
g
e
with
th
e
s
tag
es o
f
p
r
ed
ictin
g
g
r
ad
u
atio
n
:
a.
R
e
t
r
ie
v
e
At
th
is
s
tag
e,
th
e
s
im
ilar
ity
v
alu
e
is
ca
lcu
lated
u
s
in
g
th
e
c
o
s
in
e
s
im
ilar
ity
m
eth
o
d
o
n
th
e
o
ld
d
at
a
ac
co
r
d
in
g
to
th
e
in
d
ex
th
at
h
as si
m
ilar
ities
wi
th
th
e
n
ew
d
ata
en
ter
ed
.
(
,
)
=
(
)
=
.
|
|
|
|
|
|
|
|
.
=
8
|
|
|
|
=
3
.
16
|
|
|
|
=
2
.
83
(
,
)
=
8
3
.
16
.
2
.
83
=
0
.
89
An
d
th
e
r
esu
lt
o
f
ev
e
r
y
c
ase
ca
n
b
e
s
ee
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at
T
ab
le
3
.
A
s
elec
tio
n
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tag
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will
b
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ca
r
r
ie
d
o
u
t
af
ter
g
ettin
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th
e
s
im
ilar
ity
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lcu
latio
n
v
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b
e
twee
n
th
e
ca
s
es
in
th
e
ca
s
e
b
a
s
e
an
d
th
e
n
ew
ca
s
es.
I
n
th
e
s
elec
tio
n
s
tag
e,
th
e
s
im
ilar
ity
v
alu
es will b
e
s
o
r
ted
f
r
o
m
th
e
h
i
g
h
est to
th
e
lo
we
s
t v
alu
e,
an
d
th
e
h
ig
h
est v
al
u
e
will b
e
s
o
u
g
h
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
6
,
Decem
b
e
r
20
25
:
6
0
0
1
-
6
0
1
1
6006
Fro
m
T
ab
le
3
,
it
ca
n
b
e
s
ee
n
th
at
ca
s
e
n
o
.
5
h
as
th
e
h
i
g
h
est
s
im
ilar
ity
v
alu
e
with
th
e
n
ew
ca
s
e
en
ter
ed
.
T
h
e
C
B
R
s
y
s
tem
will
r
ec
o
m
m
en
d
ca
s
e
n
o
.
5
as a
s
o
lu
tio
n
.
T
o
e
v
alu
ate
th
e
d
ia
g
n
o
s
tic
p
er
f
o
r
m
an
ce
o
f
an
alg
o
r
ith
m
,
t
h
e
b
est
alg
o
r
i
th
m
is
o
n
e
th
at
n
o
t
o
n
ly
d
e
m
o
n
s
tr
ates
s
tr
o
n
g
p
er
f
o
r
m
an
ce
b
u
t
also
h
as
th
e
p
o
ten
tial to
ac
cu
r
ately
d
iag
n
o
s
e
d
ata.
T
ab
le
3
.
S
i
m
i
l
a
r
i
t
y
r
es
u
l
ts
No
G
P
A
G
e
n
d
e
r
GP
R
e
c
o
mm
e
n
d
a
t
i
o
n
S
i
m (x
,
y)
1
q
q
q
b
0
.
89
2
q
p
q
b
0
.
84
3
r
q
q
b
0
.
96
4
q
q
r
b
0
.
95
5
q
q
q
b
0
.
99
6
q
q
q
b
0
.
89
7
r
q
s
c
0
.
83
8
r
p
r
c
0
.
83
9
q
p
p
d
0
.
80
10
r
q
s
d
0
.
80
b.
R
e
u
s
e
R
eu
s
e
is
a
s
tag
e
in
ca
s
e
-
b
ase
d
r
ea
s
o
n
in
g
wh
er
e
,
at
th
is
s
ta
g
e,
th
e
ca
s
es
s
to
r
ed
in
th
e
ca
s
e
b
ase
ar
e
r
etr
iev
ed
to
b
e
u
s
ed
as
a
s
o
lu
tio
n
[
2
0
]
,
[
2
1
]
.
T
h
e
cr
iter
ia
f
o
r
s
elec
tin
g
a
ca
s
e
ar
e
ca
s
es
with
th
e
h
ig
h
est
ca
lcu
latio
n
r
esu
lts
ca
r
r
ie
d
o
u
t
in
t
h
e
p
r
ev
io
u
s
s
tag
e,
n
a
m
el
y
r
etr
iev
e
.
B
ased
o
n
t
h
e
ca
lc
u
latio
n
s
in
T
ab
le
3
,
o
n
e
o
ld
ca
s
e
was o
b
tain
ed
th
at
h
ad
th
e
h
ig
h
est lev
el
o
f
s
im
ilar
ity
to
th
e
n
ew
ca
s
e
co
m
p
ar
ed
to
th
e
o
th
er
ca
s
es,
n
am
ely
ca
s
e
n
o
.
5
,
with
a
s
im
ilar
ity
v
alu
e
o
f
0
.
9
9
.
So
,
th
e
p
r
ed
icted
r
esu
lts
o
b
tain
e
d
f
o
r
th
e
n
ew
ca
s
e
with
GPA=3
.
5
0
ar
e
g
r
ad
u
atin
g
with
a
s
tu
d
y
p
er
io
d
o
f
4
.
5
-
5
y
ea
r
s
.
c.
R
e
v
is
e
T
h
e
r
ev
is
io
n
s
tag
e
is
th
e
p
r
o
ce
s
s
o
f
r
ev
iewin
g
th
e
ca
s
e
an
d
th
e
s
o
lu
tio
n
s
p
r
o
v
i
d
ed
.
I
f
th
er
e
ar
e
er
r
o
r
s
,
th
en
im
p
r
o
v
em
e
n
ts
will
b
e
m
ad
e
to
o
v
er
co
m
e
th
e
e
r
r
o
r
s
th
at
o
cc
u
r
.
E
x
p
e
r
ts
ca
r
r
y
o
u
t
th
e
r
ev
is
io
n
p
r
o
ce
s
s
.
E
x
p
er
ts
ca
n
u
s
e
th
e
r
e
-
in
s
tan
tiatio
n
m
eth
o
d
to
ad
ap
t
ca
s
es/re
v
is
io
n
s
.
I
f
th
e
s
o
lu
tio
n
o
r
s
y
s
tem
p
r
ed
ictio
n
r
esu
lts
ar
e
co
r
r
ec
t w
ith
th
e
ac
tu
al
g
r
ad
u
atio
n
tim
e,
th
en
th
er
e
is
n
o
n
ee
d
to
r
ev
is
e,
an
d
th
e
n
ew
s
o
lu
tio
n
ca
n
b
e
d
ir
ec
tly
s
to
r
ed
in
th
e
k
n
o
wled
g
e
b
ase.
Ho
wev
er
,
if
th
e
p
r
e
d
ictio
n
r
esu
lts
d
o
n
o
t
m
atch
th
e
g
r
ad
u
atio
n
tim
e,
a
r
ev
is
io
n
o
f
t
h
e
g
r
a
d
u
atio
n
tim
e
is
ca
r
r
ied
o
u
t a
n
d
th
e
n
s
to
r
ed
in
th
e
k
n
o
wled
g
e
b
ase
[
1
4
]
,
[
2
2
]
.
d.
R
e
t
ai
n
Af
ter
th
e
r
ev
is
io
n
p
r
o
ce
s
s
is
co
m
p
lete
a
n
d
a
g
en
u
in
el
y
c
o
r
r
ec
t
s
o
lu
tio
n
h
as
b
ee
n
f
o
u
n
d
,
th
e
ex
p
er
t
will
ad
d
th
e
n
ew
ca
s
e
d
ata
th
at
h
as
b
ee
n
f
o
u
n
d
to
th
e
k
n
o
wl
ed
g
e
b
ase,
wh
ich
will
b
e
s
to
r
ed
as
s
tu
d
en
t
r
ec
o
r
d
d
ata.
Ho
wev
er
,
if
th
e
s
o
lu
tio
n
to
th
e
n
ew
ca
s
e
alr
ea
d
y
ex
is
ts
in
th
e
k
n
o
wled
g
e
b
ase,
it
d
o
es
n
o
t
n
ee
d
to
b
e
ad
d
ed
b
ec
au
s
e
th
e
r
e
will
b
e
d
u
p
licatio
n
o
f
d
ata/so
lu
tio
n
s
[
2
3
]
,
[
2
4
]
.
New
ca
s
e
d
ata
n
o
t
y
e
t
in
th
e
k
n
o
wled
g
e
b
ase
ca
n
b
e
u
s
ed
later
f
o
r
th
e
n
ex
t
ca
s
e.
T
h
is
p
r
o
ce
s
s
is
ca
l
led
th
e
r
etain
p
r
o
ce
s
s
.
2
6
0
d
atasets
wer
e
d
iv
id
ed
in
to
1
8
1
tr
ain
i
n
g
d
ata,
o
r
7
0
%
an
d
7
8
test
d
ata,
o
r
3
0
%.
T
h
e
attr
ib
u
tes
u
s
ed
ar
e
GPA
s
em
e
s
ter
4
,
g
en
d
er
,
a
n
d
GPA
s
em
ester
2
.
T
h
r
o
u
g
h
th
e
in
d
ex
i
n
g
p
r
o
ce
s
s
,
1
0
r
u
les
wer
e
o
b
tain
e
d
t
h
at
will
b
e
u
s
ed
f
o
r
t
h
e
r
etr
iev
al
p
r
o
ce
s
s
u
s
in
g
c
o
s
in
e
s
im
ilar
ity
.
New
ca
s
es
will
b
e
ca
lcu
late
d
f
o
r
s
im
ilar
ity
b
ased
o
n
th
e
i
n
d
ex
in
g
r
esu
lts
.
Fo
r
ex
am
p
le,
in
t
h
e
p
r
ev
io
u
s
ch
a
p
ter
,
s
tu
d
e
n
ts
with
a
GPA
o
f
s
em
ester
2
=2
.
3
0
a
n
d
a
GPA
o
f
s
em
ester
4
=3
.
5
0
with
m
ale
g
e
n
d
er
wer
e
c
alcu
l
ated
u
s
in
g
th
e
c
o
s
in
e
s
im
ilar
ity
m
eth
o
d
.
T
h
e
attr
ib
u
te
v
alu
e
s
,
n
am
ely
GPA
an
d
GPA,
wer
e
co
n
v
er
ted
to
f
ac
ili
tate
th
e
ca
lcu
latio
n
p
r
o
ce
s
s
,
a
n
d
th
e
g
e
n
d
er
attr
ib
u
te
v
alu
e
was
f
ir
s
t
co
n
v
er
ted
in
to
an
ac
tu
al
v
alu
e.
T
h
e
r
esu
l
ts
o
f
ca
lcu
latin
g
th
e
ca
s
e
s
im
i
lar
ity
v
alu
e
wer
e
o
b
tain
e
d
at
0
.
9
9
o
r
9
9
%
with
a
r
ec
o
m
m
en
d
ed
s
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d
y
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er
i
o
d
o
f
4
.
5
-
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y
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r
s
.
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ased
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n
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ese
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e
ac
cu
r
ac
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r
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n
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o
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h
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Fu
r
th
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o
r
e
,
f
r
o
m
th
is
tem
p
o
r
ar
y
s
o
lu
tio
n
,
r
e
v
is
in
g
s
tu
d
en
t
g
r
ad
u
atio
n
p
r
ed
ictio
n
s
ca
n
n
o
t
b
e
u
s
ed
b
ec
au
s
e
it
waits
f
o
r
th
e
s
tu
d
e
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t
to
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ad
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ate.
I
f
th
e
p
r
ed
ictio
n
r
esu
lt
is
co
r
r
ec
t,
th
en
th
e
p
r
ed
i
ctio
n
r
esu
lt
ca
n
b
e
s
to
r
ed
in
th
e
ca
s
e
b
ase
[
2
5
]
,
[
2
6
]
.
Ho
wev
er
,
if
th
e
p
r
ed
ictio
n
r
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d
o
n
o
t
m
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h
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en
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y
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e
ex
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er
t
r
e
v
is
es
th
e
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r
ed
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d
s
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es
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o
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a
ca
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e
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asis
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T
h
e
h
ig
h
est
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o
f
k
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d
6
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7
2
7
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d
t
h
e
av
e
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ag
e
is
6
3
.
5
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5
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Fo
r
t
h
e
h
ig
h
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ased
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a
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Fig
u
r
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Fig
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r
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Sy
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DIS
CU
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I
O
N
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p
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r
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'
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an
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o
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ith
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ith
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ata
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PS
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V,
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ith
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T
h
e
n
e
u
r
al
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r
k
m
eth
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d
p
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ce
s
an
ac
cu
r
ac
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v
alu
e
o
f
9
0
.
4
1
%
[
2
7
]
.
Fu
r
th
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m
o
r
e
,
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esear
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d
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o
m
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ar
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if
icatio
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ith
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o
f
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ata
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in
in
g
to
p
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ed
ict
th
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g
r
ad
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atio
n
o
f
s
tu
d
e
n
ts
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tim
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with
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r
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lem
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h
e
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er
ce
n
tag
e
o
f
s
tu
d
en
ts
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o
g
r
ad
u
ate
o
n
tim
e
.
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h
e
m
eth
o
d
co
m
p
ar
es
th
e
d
e
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o
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tr
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alg
o
r
ith
m
,
n
aiv
e
B
ay
es,
ANN,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
SVM)
,
an
d
lo
g
is
tic
r
eg
r
ess
io
n
(
L
R
)
with
t
h
e
attr
ib
u
tes
u
s
ed
:
f
ac
u
lty
,
g
e
n
d
er
,
a
g
e,
an
d
GPA
s
em
ester
I
-
I
V.
T
h
e
r
esu
lts
ar
e
th
e
ac
cu
r
ac
y
o
f
th
e
d
ec
is
io
n
t
r
ee
alg
o
r
ith
m
8
0
.
0
1
%,
n
aiv
e
B
ay
es
7
5
.
1
6
%,
ANN
1
0
0
%,
SVM
1
0
0
%,
an
d
L
R
100%
[
2
8
]
–
[
3
0
]
.
I
n
th
e
f
o
llo
win
g
y
ea
r
,
a
s
tu
d
y
en
titl
ed
P
r
ed
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g
o
n
-
tim
e
g
r
ad
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atio
n
f
o
r
n
ew
s
tu
d
en
ts
with
d
ata
m
in
in
g
with
th
e
p
r
o
b
lem
b
ein
g
t
h
e
n
u
m
b
er
o
f
s
tu
d
en
ts
wh
o
wer
e
a
b
le
to
c
o
m
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lete
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ies
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n
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e
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th
e
2
0
1
9
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2
0
2
4
p
e
r
io
d
wa
s
les
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th
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0
%
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o
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r
ly
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f
o
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ts
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e
n
ee
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ed
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f
i
n
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o
u
t
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at
p
ar
am
eter
s
in
f
lu
en
ce
d
a
s
tu
d
e
n
t
to
b
e
a
b
le
to
co
m
p
lete
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eir
s
tu
d
ies
o
n
tim
e.
Fr
o
m
th
e
test
r
esu
lts
u
s
in
g
attr
ib
u
tes
o
f
g
en
d
er
,
r
elig
io
n
,
NE
M,
m
ajo
r
,
an
d
p
r
o
f
ess
io
n
b
y
ap
p
ly
i
n
g
th
e
k
-
NN
m
et
h
o
d
a
n
d
u
s
in
g
s
am
p
le
d
ata
f
r
o
m
alu
m
s
o
f
th
e
2
0
1
7
-
2
0
2
2
g
r
a
d
u
atio
n
y
ea
r
s
f
o
r
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ld
ca
s
es
an
d
alu
m
s
d
ata
o
f
th
e
2
0
2
3
g
r
ad
u
atio
n
y
ea
r
s
f
o
r
n
ew
ca
s
es,
an
ac
cu
r
ac
y
le
v
el
o
f
8
3
.
3
6
%
was
o
b
tain
ed
[
3
1
]
.
I
n
th
e
s
am
e
y
ea
r
,
a
s
tu
d
y
e
n
titl
ed
Pre
d
ictin
g
Stu
d
en
t
Gr
ad
u
atio
n
u
s
in
g
th
e
k
-
NN
m
eth
o
d
was
co
n
d
u
cted
b
y
[
3
2
]
.
T
h
e
p
r
o
b
lem
was
th
e
lo
w
p
er
ce
n
tag
e
o
f
s
tu
d
e
n
ts
wh
o
g
r
a
d
u
ated
o
n
tim
e,
s
o
th
i
s
s
tu
d
y
aim
ed
to
d
eter
m
i
n
e
th
e
p
er
ce
n
tag
e
v
alu
e
o
f
s
tu
d
en
t g
r
ad
u
atio
n
u
s
in
g
th
e
k
-
NN
m
eth
o
d
.
I
n
th
e
k
-
NN
m
eth
o
d
,
th
e
d
ata
u
s
ed
in
th
e
p
r
ed
ictio
n
is
1
6
7
d
ata
a
n
d
7
attr
ib
u
tes,
n
am
ely
g
en
d
er
,
r
esid
en
ce
s
tatu
s
,
tr
a
n
s
p
o
r
tatio
n
s
tatu
s
,
m
ar
ital
s
tatu
s
,
r
eg
io
n
al
o
r
ig
in
,
s
ch
o
o
l
ty
p
e,
an
d
Un
d
a
n
a
en
tr
an
ce
r
o
u
te.
T
h
e
ac
cu
r
ac
y
v
alu
e
u
s
in
g
th
e
k
-
NN
m
eth
o
d
is
8
0
%
[
3
3
]
,
[
3
4
]
.
Fu
r
th
er
r
esear
c
h
en
titl
ed
k
-
N
N
alg
o
r
ith
m
m
o
d
el
f
o
r
s
tu
d
en
t
g
r
ad
u
atio
n
p
r
ed
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n
with
t
h
e
p
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b
lem
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ein
g
th
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h
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c
a
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t
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te
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m
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:
ra
t
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y
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l
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k
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g
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l
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a
c
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i
d
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u
k
A
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iy
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ti
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ia
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t
o
h
a
s
o
v
e
r
2
4
y
e
a
rs
o
f
e
x
p
e
rien
c
e
in
th
e
ICT
i
n
d
u
stry
,
with
e
x
p
e
rti
se
i
n
b
u
si
n
e
ss
d
e
v
e
lo
p
m
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n
t,
g
o
v
e
r
n
m
e
n
t
re
lati
o
n
s,
c
o
rp
o
ra
te
a
ffa
irs,
c
u
sto
m
e
r
e
n
g
a
g
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m
e
n
t,
fi
n
a
n
c
e
,
tec
h
n
ica
l
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p
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ra
ti
o
n
s,
p
r
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jec
t
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n
d
p
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p
le
m
a
n
a
g
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m
e
n
t,
a
n
d
re
so
u
rc
e
m
o
b
il
iza
ti
o
n
.
S
h
e
is
a
lso
e
x
p
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rien
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e
d
in
g
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rn
a
n
c
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p
ra
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ti
c
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s
b
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se
d
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n
IS
O
2
7
0
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1
a
n
d
IS
O
9
0
0
1
:
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0
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5
sta
n
d
a
rd
s.
T
h
ro
u
g
h
o
u
t
h
e
r
c
a
re
e
r,
sh
e
h
a
s
b
e
e
n
in
v
o
l
v
e
d
in
v
a
rio
u
s
stra
teg
ic
in
it
iati
v
e
s
to
su
p
p
o
rt
o
rg
a
n
iza
ti
o
n
a
l
g
ro
wth
a
n
d
o
p
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ra
ti
o
n
a
l
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x
c
e
ll
e
n
c
e
,
p
a
rti
c
u
larly
i
n
a
li
g
n
in
g
tec
h
n
o
l
o
g
y
wit
h
b
u
sin
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ss
o
b
jec
ti
v
e
s.
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r
stro
n
g
b
a
c
k
g
ro
u
n
d
i
n
b
o
th
tec
h
n
ica
l
a
n
d
m
a
n
a
g
e
rial
a
sp
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c
ts
e
n
a
b
les
h
e
r
to
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o
n
tri
b
u
t
e
e
ffe
c
ti
v
e
ly
to
th
e
su
c
c
e
ss
o
f
ICT
p
ro
jec
ts
a
n
d
c
o
r
p
o
ra
t
e
g
o
v
e
r
n
a
n
c
e
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
v
ia em
a
il
a
t:
ti
n
u
k
.
a
n
d
riy
a
n
ti
@e
sa
u
n
g
g
u
l
.
a
c
.
id
.
De
wi
S
e
tio
wa
ti
re
c
e
iv
e
d
h
e
r
M
.
Tr.
Ko
m
.
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
P
o
li
tek
n
i
k
El
e
k
tr
o
n
ik
a
Ne
g
e
ri
S
u
ra
b
a
y
a
.
S
h
e
is
a
lec
tu
re
r
a
t
th
e
De
p
a
rtme
n
t
o
f
In
f
o
rm
a
ti
c
s
En
g
i
n
e
e
rin
g
,
F
a
c
u
lt
y
o
f
Co
m
p
u
t
e
r
S
c
ien
c
e
,
Un
iv
e
rsitas
Esa
Un
g
g
u
l,
Ja
k
a
rta,
I
n
d
o
n
e
sia
.
He
r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
o
b
jec
t
-
o
rien
ted
p
ro
g
ra
m
m
in
g
,
S
QL
,
we
b
d
e
v
e
lo
p
m
e
n
t,
so
ftwa
re
d
e
v
e
lo
p
m
e
n
t,
a
n
d
C+
+
.
S
h
e
is
a
c
ti
v
e
ly
in
v
o
l
v
e
d
in
tea
c
h
in
g
a
n
d
re
se
a
rc
h
a
c
ti
v
it
ies
re
late
d
t
o
th
e
se
field
s
a
n
d
is
d
e
d
ica
ted
t
o
e
n
h
a
n
c
in
g
st
u
d
e
n
ts’
k
n
o
wle
d
g
e
a
n
d
sk
il
ls
in
so
ftwa
re
e
n
g
in
e
e
rin
g
a
n
d
in
f
o
rm
a
ti
o
n
tec
h
n
o
l
o
g
y
.
S
h
e
a
lso
p
a
rti
c
i
p
a
tes
in
a
c
a
d
e
m
ic
in
it
iativ
e
s
t
o
su
p
p
o
rt
t
h
e
d
e
v
e
l
o
p
m
e
n
t
o
f
d
ig
it
a
l
c
o
m
p
e
ten
c
ies
in
h
ig
h
e
r
e
d
u
c
a
ti
o
n
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
v
ia
e
m
a
il
a
t:
d
e
wi.
se
ti
o
wa
ti
@e
sa
u
n
g
g
u
l.
a
c
.
i
d
.
Ra
n
n
y
Meil
isa
re
c
e
iv
e
d
h
e
r
M
.
P
d
.
T.
d
e
g
re
e
in
t
e
c
h
n
ic
fro
m
Un
iv
e
rsitas
Ne
g
e
ri
P
a
d
a
n
g
.
S
h
e
is
a
lec
tu
re
r
a
t
th
e
De
p
a
rtme
n
t
o
f
In
f
o
rm
a
ti
c
s
En
g
in
e
e
rin
g
,
F
a
c
u
lt
y
o
f
Co
m
p
u
te
r
S
c
ien
c
e
,
Un
iv
e
rsitas
Esa
Un
g
g
u
l,
Ja
k
a
rta,
In
d
o
n
e
sia
.
He
r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
i
n
fo
rm
a
ti
c
s
e
n
g
in
e
e
rin
g
,
p
r
o
g
ra
m
m
in
g
lan
g
u
a
g
e
s,
v
o
c
a
ti
o
n
a
l
e
d
u
c
a
ti
o
n
,
a
n
d
in
stru
c
ti
o
n
a
l
m
e
d
ia.
S
h
e
is
a
c
ti
v
e
ly
e
n
g
a
g
e
d
in
tea
c
h
in
g
a
n
d
re
se
a
rc
h
a
c
ti
v
it
ies
re
late
d
t
o
t
h
e
se
field
s,
f
o
c
u
sin
g
o
n
e
n
h
a
n
c
in
g
th
e
q
u
a
li
t
y
o
f
e
d
u
c
a
ti
o
n
th
r
o
u
g
h
i
n
n
o
v
a
ti
v
e
lea
rn
in
g
m
e
th
o
d
s
a
n
d
t
h
e
in
te
g
ra
ti
o
n
o
f
tec
h
n
o
l
o
g
y
.
S
h
e
a
lso
c
o
n
tri
b
u
t
e
s
to
th
e
d
e
v
e
lo
p
m
e
n
t
o
f
in
st
ru
c
ti
o
n
a
l
m
e
d
ia
to
s
u
p
p
o
rt
e
ffe
c
ti
v
e
lea
rn
in
g
i
n
v
o
c
a
ti
o
n
a
l
a
n
d
h
i
g
h
e
r
e
d
u
c
a
ti
o
n
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
v
ia
e
m
a
il
a
t:
m
e
il
isa
.
ra
n
n
y
a
@g
m
a
il
.
c
o
m
.
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