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m
s
[
6
]
.
A
s
a
r
es
u
lt,
m
o
r
e
m
e
n
tal
h
ea
lt
h
is
s
u
es
o
f
h
i
g
h
er
lev
els
ar
e
b
ein
g
r
ep
o
r
ted
n
o
w
.
Am
o
n
g
p
r
e
-
u
n
i
v
er
s
it
y
s
t
u
d
en
t
s
in
B
a
n
g
lad
esh
,
d
ep
r
ess
io
n
a
n
d
an
x
iet
y
r
ates
o
f
4
4
%
an
d
2
7
%,
r
esp
ec
tiv
el
y
,
h
av
e
b
ee
n
r
ep
o
r
ted
[
7
]
,
b
u
t
th
ese
r
ates
h
av
e
escalate
d
to
5
2
%
an
d
5
8
%,
r
esp
ec
tiv
el
y
[
8
]
.
C
u
r
r
en
tl
y
,
t
h
is
is
a
w
o
r
ld
w
id
e
is
s
u
e
t
h
at
tr
an
s
ce
n
d
s
g
eo
g
r
ap
h
ical
b
o
u
n
d
ar
ies.
A
cc
o
r
d
in
g
to
r
esear
ch
,
th
er
e
w
a
s
co
n
ce
r
n
ab
o
u
t
th
e
r
i
s
e
i
n
s
tu
d
e
n
t
d
ep
r
ess
io
n
ac
r
o
s
s
v
ar
i
o
u
s
A
s
ian
co
u
n
tr
ie
s
i
n
2
0
2
0
,
w
it
h
I
n
d
ia
r
ep
o
r
tin
g
a
p
r
ev
alen
ce
o
f
3
1
.
9
%
am
o
n
g
m
ed
ical
s
tu
d
e
n
ts
[
9
]
.
I
n
ad
d
itio
n
,
th
e
W
HO
f
o
r
ec
ast
s
th
at
o
v
er
5
4
m
illi
o
n
in
d
iv
id
u
als
in
C
h
i
n
a
s
u
f
f
er
f
r
o
m
d
ep
r
ess
io
n
,
w
h
er
ea
s
ap
p
r
o
x
i
m
ate
l
y
4
1
m
illi
o
n
p
eo
p
le
s
u
f
f
er
f
r
o
m
an
x
iet
y
d
is
o
r
d
er
s
[
1
0
]
.
I
n
B
an
g
lad
es
h
,
a
r
esear
ch
i
n
v
e
s
ti
g
atio
n
f
o
u
n
d
a
d
is
t
u
r
b
in
g
r
ate
o
f
s
u
icid
al
id
ea
tio
n
an
d
atte
m
p
ts
a
m
o
n
g
y
o
u
n
g
ad
u
l
ts
,
h
ig
h
li
g
h
tin
g
t
h
e
n
ee
d
f
o
r
i
m
p
r
o
v
ed
m
e
n
tal
h
ea
l
th
s
u
p
p
o
r
t
s
er
v
ices
[
1
1
]
.
A
n
esti
m
a
ted
2
5
%
o
f
th
e
w
o
r
ld
’
s
p
o
p
u
latio
n
s
u
f
f
er
f
r
o
m
m
en
tal
h
ea
lth
d
i
s
ea
s
es,
w
h
er
ea
s
ap
p
r
o
x
i
m
atel
y
7
m
illi
o
n
B
an
g
lad
es
h
is
s
u
f
f
er
f
r
o
m
a
n
x
iet
y
an
d
d
ep
r
ess
io
n
.
Su
icid
e
i
s
th
e
m
o
s
t
co
n
ce
r
n
i
n
g
co
n
s
eq
u
e
n
ce
o
f
d
ep
r
ess
io
n
.
T
h
e
W
HO
an
ticip
ated
th
at
7
0
3
,
0
0
0
in
d
iv
id
u
al
s
w
o
u
ld
d
ie
an
n
u
all
y
f
r
o
m
s
u
icid
e
w
o
r
ld
w
id
e
in
2
0
2
0
[
1
2
]
.
Nu
m
er
o
u
s
f
ac
to
r
s
,
n
a
m
el
y
ac
ad
e
m
ic
o
r
n
o
n
-
ac
ad
e
m
ic
p
r
ess
u
r
es
s
u
ch
as
s
o
cio
ec
o
n
o
m
ic,
en
v
ir
o
n
m
e
n
tal,
c
u
lt
u
r
al,
an
d
p
s
y
c
h
o
lo
g
ica
l a
ttrib
u
tes,
m
a
y
c
au
s
e
s
tr
ess
a
m
o
n
g
y
o
u
th
s
[
1
3
]
.
T
h
e
tr
ad
itio
n
al
d
iag
n
o
s
i
s
o
f
d
ep
r
ess
io
n
r
elies
o
n
cli
n
ical
tr
e
at
m
e
n
t,
an
d
s
el
f
-
ad
m
i
n
i
s
ter
ed
m
ea
s
u
r
es
ar
e
s
u
b
j
ec
tiv
e
an
d
ti
m
e
-
co
n
s
u
m
in
g
.
W
ith
r
ec
en
t
d
e
v
elo
p
m
en
ts
i
n
b
o
th
m
ed
ical
r
esear
ch
an
d
tech
n
o
lo
g
y
,
m
ac
h
in
e
lear
n
in
g
(
ML
)
h
as
g
r
ad
u
all
y
s
u
p
p
lan
ted
m
o
r
e
co
n
v
e
n
tio
n
al
m
et
h
o
d
s
f
o
r
d
iag
n
o
s
i
n
g
a
n
d
tr
ea
tin
g
d
ep
r
ess
io
n
.
M
L
ca
n
p
r
o
ce
s
s
v
ast
a
m
o
u
n
ts
o
f
d
ata,
p
o
ten
ti
all
y
lead
i
n
g
to
ea
r
lier
d
etec
ti
o
n
,
m
o
r
e
ac
c
u
r
ate
d
iag
n
o
s
e
s
,
an
d
i
m
p
r
o
v
ed
tr
ea
t
m
e
n
t
o
u
tco
m
es
[
1
4
]
.
Stu
d
ie
s
u
s
i
n
g
M
L
al
g
o
r
ith
m
s
ca
n
a
n
al
y
ze
v
ar
io
u
s
d
ata
s
o
u
r
ce
s
,
in
cl
u
d
in
g
cli
n
ical
r
ec
o
r
d
s
,
s
o
cial
m
ed
ia
ac
tiv
it
y
,
an
d
s
p
ee
ch
p
atter
n
s
,
to
id
en
tify
in
d
iv
id
u
als
at
r
is
k
f
o
r
d
ep
r
ess
io
n
[
1
5
]
.
C
o
n
v
e
n
ti
o
n
al
ML
m
o
d
el
s
ar
e
p
ar
ticu
lar
l
y
co
m
p
licated
,
as
ar
e
en
s
e
m
b
le
ap
p
r
o
ac
h
es
th
at
f
r
eq
u
en
tl
y
ac
t
as
“
b
lac
k
b
o
x
es.
”
B
ec
au
s
e
o
f
t
h
is
lac
k
o
f
tr
an
s
p
ar
en
c
y
,
it
i
s
d
i
f
f
icu
lt
to
u
n
d
er
s
ta
n
d
t
h
e
p
r
ed
ictio
n
g
en
er
atio
n
p
r
o
ce
s
s
[
5
]
,
[
1
6
]
.
C
o
n
s
eq
u
en
tl
y
,
e
x
p
lain
ab
le
ar
ti
f
icial
i
n
tell
ig
e
n
ce
(
XA
I
)
tec
h
n
iq
u
es
o
f
f
er
in
s
ig
h
t
in
to
h
o
w
m
o
d
el
s
o
b
tain
th
eir
f
in
d
i
n
g
s
.
Fo
r
e
x
a
m
p
le,
s
h
ap
le
y
ad
d
itiv
e
ex
p
lan
atio
n
s
(
SH
A
P
)
v
alu
e
s
ca
n
e
m
p
h
a
s
ize
w
h
ic
h
clin
ical
f
ac
to
r
s
co
n
tr
ib
u
te
th
e
m
o
s
t
to
a
s
p
ec
if
ic
d
iag
n
o
s
is
,
m
ak
in
g
th
e
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
m
o
r
e
tr
an
s
p
ar
en
t.
T
h
is
s
tu
d
y
b
r
id
g
es
t
h
e
g
ap
b
et
w
ee
n
p
r
ed
ictiv
e
ac
cu
r
ac
y
a
n
d
m
o
d
el
in
ter
p
r
etab
ilit
y
b
y
in
te
g
r
atin
g
SH
A
P
-
b
ased
ex
p
lain
ab
ili
t
y
i
n
t
o
d
e
p
r
ess
io
n
s
ev
er
it
y
c
lass
if
ic
atio
n
u
s
i
n
g
s
tr
u
ct
u
r
ed
p
s
y
ch
o
l
o
g
ical
s
u
r
v
e
y
d
ata.
I
t
also
atte
m
p
ts
to
p
r
o
v
id
e
in
s
ig
h
t
in
to
t
h
e
m
u
ltip
le
asp
ec
ts
o
f
d
ep
r
ess
io
n
to
b
r
in
g
atten
tio
n
to
th
is
s
ig
n
i
f
ica
n
t
p
u
b
lic
h
ea
lt
h
co
n
ce
r
n
.
B
y
co
n
d
u
ctin
g
a
t
h
o
r
o
u
g
h
ex
a
m
i
n
a
ti
o
n
o
f
th
e
f
ac
to
r
s
t
h
at
co
n
tr
ib
u
t
e
to
d
ep
r
ess
io
n
,
th
e
ef
f
ec
ts
it
h
as,
an
d
t
h
e
p
o
s
s
ib
le
r
e
m
ed
ies.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
I
n
o
r
d
er
to
ad
d
r
ess
th
e
d
ep
r
ess
io
n
,
m
a
n
y
r
esear
c
h
er
s
s
t
u
d
ied
an
d
p
r
o
p
o
s
ed
th
eir
m
et
h
o
d
o
lo
g
y
to
f
in
d
o
u
t
th
e
lev
el
f
o
r
en
s
u
r
i
n
g
p
r
o
p
er
g
u
id
an
ce
f
o
r
a
p
atien
t.
L
i
[
1
7
]
u
tili
ze
d
f
o
u
r
d
is
tin
ct
ML
m
o
d
els,
h
ig
h
lig
h
ti
n
g
th
e
u
r
g
e
n
t
w
o
r
ld
w
id
e
is
s
u
e
o
f
d
ep
r
ess
io
n
an
d
s
u
icid
e
an
d
u
n
d
er
lin
i
n
g
th
e
cr
u
cial
r
eq
u
ir
e
m
en
t
f
o
r
p
r
o
ac
tiv
e
m
en
tal
h
ea
lt
h
in
ter
v
e
n
tio
n
s
.
I
n
th
is
s
t
u
d
y
t
h
e
y
u
s
ed
d
atasets
p
r
o
v
id
ed
b
y
“
S
u
icid
e
W
atch
”
an
d
“
Dep
r
ess
io
n
”
o
n
th
e
R
ed
d
it
p
latf
o
r
m
a
n
d
em
p
lo
y
ed
a
d
ee
p
n
eu
r
al
n
et
w
o
r
k
(
DNN
)
m
o
d
el
to
clas
s
if
y
t
h
e
lev
el
o
f
d
ep
r
ess
io
n
th
at
ac
h
ie
v
ed
9
5
%
ac
cu
r
ac
y
.
B
ir
ad
ar
an
d
T
o
tad
[
1
8
]
h
ig
h
li
g
h
t
t
h
e
g
r
o
w
in
g
u
tili
za
tio
n
o
f
T
w
itter
an
d
o
th
er
s
o
cial
n
et
w
o
r
k
in
g
s
ites
(
SNS)
as
p
latf
o
r
m
s
f
o
r
ex
p
r
ess
in
g
e
m
o
tio
n
s
an
d
d
ail
y
ac
ti
v
itie
s
,
p
r
o
v
id
in
g
i
m
p
o
r
tan
t
d
ata
f
o
r
p
s
y
c
h
o
lo
g
ical
r
e
s
ea
r
ch
.
R
e
s
ea
r
ch
er
s
h
a
v
e
u
s
ed
a
b
ac
k
p
r
o
p
ag
atio
n
n
eu
r
al
n
e
t
w
o
r
k
(
B
P
NN)
to
class
i
f
y
t
w
ee
ts
a
s
eith
er
i
n
d
ica
tiv
e
o
f
d
ep
r
ess
io
n
o
r
n
o
t.
A
l
m
ar
s
et
a
l
.
[
1
9
]
co
llected
a
d
a
taset
f
r
o
m
T
w
itter
,
w
h
ic
h
co
n
s
i
s
ted
o
f
ar
o
u
n
d
6
0
0
0
tw
ee
t
s
,
f
o
r
an
al
y
s
is
o
f
th
e
p
eo
p
le’
s
d
ep
r
ess
io
n
le
v
el.
Si
m
ilar
l
y
,
Z
u
l
f
i
k
e
r
et
a
l
.
[
2
0
]
also
w
o
r
k
ed
in
t
h
e
s
i
m
ilar
d
o
m
ain
.
T
h
ey
u
s
ed
s
y
n
th
e
tic
m
in
o
r
it
y
o
v
er
s
a
m
p
li
n
g
tech
n
iq
u
e
(
SM
OT
E
)
t
o
eli
m
in
ate
th
e
cla
s
s
i
m
b
a
lan
ce
p
r
o
b
le
m
i
n
th
eir
d
ataset.
Af
ter
t
h
at,
th
e
r
esear
ch
er
s
e
m
p
lo
y
ed
th
r
ee
ML
al
g
o
r
ith
m
s
:
ad
ap
tiv
e
b
o
o
s
tin
g
(
A
d
aB
o
o
s
t
)
,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
(
SV
M
)
,
an
d
lo
g
is
tic
r
eg
r
ess
io
n
(
LR
)
to
class
i
f
y
d
ep
r
ess
io
n
p
atien
t
s
,
an
d
A
d
aB
o
o
s
t
o
u
tp
er
f
o
r
m
ed
th
e
o
t
h
er
s
w
it
h
an
ac
cu
r
ac
y
o
f
9
2
.
5
6
%.
Haq
u
e
et
a
l
.
[
2
1
]
in
tr
o
d
u
ce
d
th
e
B
o
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ith
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ated
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w
it
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f
9
5
%.
Si
m
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P
r
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y
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et
al
.
[
2
2
]
f
o
cu
s
ed
o
n
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atel
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s
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f
y
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Naï
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ay
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tp
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r
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ed
Evaluation Warning : The document was created with Spire.PDF for Python.
T
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s
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et
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l
.
[
2
4
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f
o
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ased
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2
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f
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m
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ased
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t f
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Ki
m
[
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s
u
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ML
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ased
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m
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ad
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ata,
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etec
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tech
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2
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class
if
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is
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ata,
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h
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g
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d
Ma
g
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[
2
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]
ac
ce
s
s
ed
a
p
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licl
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ai
lab
le
d
ataset
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m
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a
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t M
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ith
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3.
M
E
T
H
O
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h
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s
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tio
n
co
m
p
r
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ct
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b
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el
w
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atio
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m
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ics.
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n
th
e
s
u
b
s
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t
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d
a
t
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s
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r
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o
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ti
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at
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F
ig
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1
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s
t
r
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t
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th
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t
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u
r
e
1
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o
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k
f
lo
w
o
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th
e
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o
p
o
s
ed
d
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io
n
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s
if
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y
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te
m
3
.
1
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Da
t
a
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it
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T
o
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u
ct
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h
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llected
f
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m
t
h
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n
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h
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NI
MH
)
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Dh
a
k
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B
an
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lad
es
h
[
3
0
]
.
B
ased
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e
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esti
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n
n
air
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d
ata
w
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p
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8
in
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is
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ct
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2
8
9
p
ar
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ts
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f
o
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to
h
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e
m
ild
d
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r
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d
7
3
,
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an
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w
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e
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o
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to
h
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m
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ate,
s
ev
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e,
an
d
p
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f
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n
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d
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,
r
esp
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ti
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l
y
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T
ab
le
1
co
n
s
is
ts
o
f
at
tr
ib
u
tes
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d
d
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d
ata.
Af
ter
th
at,
ac
co
r
d
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to
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e
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ir
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r
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Scale
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,
T
a
b
le
2
p
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es o
f
d
ep
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d
ep
en
d
i
n
g
o
n
p
er
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n
tiles
a
n
d
co
r
r
esp
o
n
d
in
g
s
co
r
es o
n
d
ep
r
ess
io
n
s
c
ale.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
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m
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t E
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Vo
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24
,
No
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3
,
J
u
n
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20
26
:
9
15
-
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25
918
T
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le
1
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Ov
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15
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4
U
p
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Emp
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19
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ry
20
M
a
k
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7
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21
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22
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W
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23
W
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10
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o
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24
A
p
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h
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11
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e
a
t
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25
W
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26
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13
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27
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x
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14
P
a
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f
u
n
me
t
e
x
p
e
c
t
a
t
i
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n
s
T
ab
le
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.
Sev
er
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y
o
f
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ep
r
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n
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ased
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n
th
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co
r
r
esp
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co
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o
f
d
ep
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ca
le
P
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t
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sp
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d
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c
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s o
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t
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p
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sc
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l
e
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e
v
e
r
i
t
y
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f
d
e
p
r
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ssi
o
n
25
0
-
34
M
i
l
d
d
e
p
r
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n
50
35
-
43
M
o
d
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r
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p
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75
44
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S
e
v
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e
p
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n
1
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5
1
a
n
d
a
b
o
v
e
P
r
o
f
o
u
n
d
d
e
p
r
e
ssi
o
n
3
.
2
.
Da
t
a
p
re
pro
ce
s
s
ing
Data
p
r
ep
r
o
ce
s
s
in
g
i
s
t
h
e
cr
u
cial
p
ar
t
o
f
r
esear
c
h
.
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i
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m
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in
o
u
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d
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w
e
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e
r
,
th
er
e
w
er
e
n
o
m
i
s
s
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g
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al
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s
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n
d
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r
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ity
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ased
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co
d
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m
ap
p
in
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tili
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ess
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h
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y
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ap
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h
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m
n
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h
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ied
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h
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g
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s
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8
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d
2
9
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th
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n
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m
ed
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ep
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:
0
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:
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Sev
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:
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,
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d
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r
o
f
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:
3
.
Data
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r
m
aliza
tio
n
is
th
e
p
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s
o
f
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escalin
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attr
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h
a
v
e
a
m
ea
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o
f
0
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d
a
v
ar
ian
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o
f
1
[
3
1
]
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e
ap
p
lied
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s
tan
d
ar
d
s
ca
ler
to
n
o
r
m
aliz
e
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m
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ile
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ig
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al
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g
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al
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alan
cin
g
t
h
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d
ataset
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n
h
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n
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s
m
o
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el
tr
ain
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n
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ias
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ce
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tain
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s
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ce
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to
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t
h
e
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is
k
o
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p
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o
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er
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el
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ain
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lo
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h
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E
to
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alize
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d
is
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ib
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tio
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ata
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ai
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ate
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ata
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m
a
m
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r
it
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lass
[
3
3
]
,
[
3
4
]
.
Fig
u
r
e
2
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a)
ill
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s
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ates
th
e
i
m
b
alan
ce
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atase
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d
F
ig
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r
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b
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ep
icts
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alan
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d
ataset
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a
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ter
e
m
p
lo
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g
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.
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e
d
iv
id
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e
d
ataset
in
to
t
w
o
d
is
tin
ct
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te
g
o
r
ies:
tr
ain
i
n
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(
8
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%)
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2
0
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ets.
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u
t
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f
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les
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6
s
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m
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les
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test
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g
.
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a)
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b
)
Fig
u
r
e
2
.
Vis
u
al
izatio
n
o
f
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ep
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n
s
e
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it
y
clas
s
d
is
tr
ib
u
t
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h
o
w
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n
g
:
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a)
i
m
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ala
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ce
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class
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n
d
(
b
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alan
ce
d
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ter
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ly
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SM
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Evaluation Warning : The document was created with Spire.PDF for Python.
T
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A
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w
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M
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tr
a
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A
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[
3
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d
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KN
N)
[
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,
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d
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e
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ain
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w
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th
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h
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ain
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etr
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a
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ML
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g
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=
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RE
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9
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o
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1
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2
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s
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atp
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3
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3
.
I
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th
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s
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tu
d
y
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w
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h
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d
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au
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g
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ith
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s
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ick
l
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d
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atel
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m
p
r
o
v
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n
g
t
h
e
d
ep
r
ess
io
n
p
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ed
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n
o
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tco
m
e
s
.
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r
ev
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n
g
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h
e
m
o
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el
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er
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o
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m
an
ce
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atr
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x
w
as
g
e
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ated
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ch
M
L
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o
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el.
Fig
u
r
es
3
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d
4
p
r
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w
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s
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n
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a
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o
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ala
n
ce
d
an
d
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ata.
Fo
r
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n
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u
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a
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ix
,
0
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i
ld
,
1
:
m
o
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er
ate,
2
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s
ev
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d
3
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p
r
o
f
o
u
n
d
d
ep
r
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io
n
.
I
n
Fi
g
u
r
e
3
(
a)
,
th
e
L
R
clas
s
if
ier
in
th
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“
Mild
”
class
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as
tr
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e
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e
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u
e
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alse
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f
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9
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d
1
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r
esp
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ely
.
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h
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g
u
r
e
3
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cc
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e
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ig
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e
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m
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ild
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Fig
u
r
es
3
(
c)
an
d
(
d
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o
r
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d
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d
aB
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o
s
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e
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P
v
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es
ar
e
5
9
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d
5
7
f
o
r
m
ild
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s
.
Fo
r
th
e
Fi
g
u
r
e
3
(
e)
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ier
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h
e
p
r
o
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o
u
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d
class
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P
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e
s
ar
e
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ad
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d
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n
Fi
g
u
r
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3
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f
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an
d
F
ig
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r
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3
(
g
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KNN
p
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ict
th
e
s
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m
ilar
n
u
m
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o
f
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P
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o
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ild
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s
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h
o
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g
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N
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e
s
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e
d
if
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en
t,
2
6
an
d
2
9
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
(
f
)
(
g
)
Fig
u
r
e
3
.
C
o
n
f
u
s
io
n
m
atr
ices
f
o
r
ML
m
o
d
els o
n
i
m
b
alan
ce
d
d
ata:
(
a)
L
R
,
(
b
)
SVM
,
(
c)
ex
tr
a
tr
ee
,
(
d
)
A
d
aB
o
o
s
t
,
(
e)
GB
,
(
f
)
R
F
,
an
d
(
g
)
KNN
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
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24
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No
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3
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26
:
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15
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Fig
u
r
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4
d
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n
f
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ter
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o
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g
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F
ig
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(
a)
,
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m
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,
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d
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1
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T
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ith
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i
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Fig
u
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b
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as t
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h
e
s
e
v
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e
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n
F
ig
u
r
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4
(
c)
f
o
r
e
x
tr
a
tr
ee
class
if
ier
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a
s
6
0
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T
P
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a
n
d
1
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FP
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.
T
h
e
s
i
m
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n
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m
b
er
o
f
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5
2
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w
a
s
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ted
f
o
r
s
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e
an
d
p
r
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f
o
u
n
d
class
e
s
in
th
e
A
d
aB
o
o
s
t
class
if
ier
in
F
ig
u
r
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4
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d
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.
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r
th
e
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s
if
ier
in
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ig
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r
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4
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e)
,
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e
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Evaluation Warning : The document was created with Spire.PDF for Python.
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n
ts
p
o
lled
ex
p
er
ien
ce
d
m
o
d
er
ate
an
d
s
ev
er
e
lev
els
o
f
s
e
v
er
it
y
o
f
d
ep
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ess
io
n
.
T
o
ca
r
r
y
o
u
t
th
i
s
s
tu
d
y
,
w
e
u
tili
ze
s
e
v
en
M
L
class
i
f
ier
s
to
class
i
f
y
t
h
e
l
ev
el
o
f
d
ep
r
ess
io
n
.
A
f
ter
u
ti
lizin
g
th
e
SMOT
E
tech
n
iq
u
e,
t
h
e
p
er
f
o
r
m
an
ce
o
f
ea
ch
alg
o
r
it
h
m
s
u
r
g
ed
.
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h
e
ex
tr
a
tr
ee
s
clas
s
i
f
ier
ac
h
ie
v
es
t
h
e
h
i
g
h
est
a
v
er
ag
e
ac
cu
r
ac
y
o
f
9
7
.
8
5
%,
o
u
tp
er
f
o
r
m
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n
g
s
ix
o
t
h
er
al
g
o
r
ith
m
s
,
w
h
ile
th
e
in
te
g
r
atio
n
o
f
t
h
e
SH
A
P
tech
n
iq
u
e
p
r
o
v
id
es
tr
an
s
p
ar
en
t
r
ea
s
o
n
i
n
g
b
eh
i
n
d
m
o
d
el
p
r
ed
ictio
n
s
.
T
h
e
an
al
y
s
is
r
e
v
ea
ls
th
at
tu
r
m
o
il
w
a
s
th
e
m
o
s
t
in
f
lu
e
n
tia
l
f
ea
t
u
r
e
p
o
s
itiv
el
y
c
o
r
r
elate
d
w
it
h
d
ep
r
ess
io
n
,
w
h
er
ea
s
s
ex
in
ter
est
s
h
o
w
ed
t
h
e
s
tr
o
n
g
e
s
t
n
e
g
ati
v
e
co
n
tr
ib
u
tio
n
.
T
h
ese
i
n
s
i
g
h
ts
d
e
m
o
n
s
tr
ate
th
e
p
o
ten
tia
l
o
f
X
A
I
i
n
s
u
p
p
o
r
tin
g
ea
r
l
y
d
ep
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ess
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d
etec
tio
n
a
n
d
f
o
s
ter
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g
d
ata
-
d
r
iv
e
n
m
e
n
tal
h
ea
lth
in
ter
v
en
tio
n
s
.
F
u
tu
r
e
w
o
r
k
w
ill
f
o
cu
s
o
n
ex
p
an
d
i
n
g
th
e
d
ataset
to
in
clu
d
e
d
iv
er
s
e
d
e
m
o
g
r
ap
h
ic
g
r
o
u
p
s
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d
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te
g
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ati
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g
m
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lti
m
o
d
al
f
ea
tu
r
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c
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as
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eh
a
v
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r
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d
tex
t
u
al
d
ata
to
f
u
r
t
h
er
i
m
p
r
o
v
e
p
r
ed
ictiv
e
p
er
f
o
r
m
a
n
ce
an
d
in
ter
p
r
etab
ilit
y
.
RE
F
E
R
E
NC
E
S
[
1
]
R
.
S
a
r
w
a
r
a
n
d
A
.
A
smat
,
“
M
e
n
t
a
l
h
e
a
l
t
h
e
x
p
e
r
t
’
s
p
e
r
sp
e
c
t
i
v
e
o
n
r
i
sk
a
n
d
p
r
o
t
e
c
t
i
v
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f
a
c
t
o
r
s
o
f
su
i
c
i
d
e
i
d
e
a
t
i
o
n
i
n
P
a
t
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e
n
t
s
w
i
t
h
O
C
D
a
n
d
d
e
p
r
e
ssi
o
n
,
”
BM
C
Ps
y
c
h
i
a
t
ry
,
v
o
l
.
2
5
,
n
o
.
1
,
2
0
2
5
,
d
o
i
:
1
0
.
1
1
8
6
/
s
1
2
8
8
8
-
0
2
4
-
0
6
4
0
4
-
9.
[
2
]
A
m
e
r
i
c
a
n
P
sy
c
h
o
l
o
g
i
c
a
l
A
sso
c
i
a
t
i
o
n
,
“
D
e
p
r
e
ssi
o
n
.
”
A
c
c
e
sse
d
:
A
p
r
.
1
6
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
a
p
a
.
o
r
g
/
t
o
p
i
c
s/
d
e
p
r
e
ssi
o
n
[
3
]
A
.
M
.
D
e
l
a
mat
e
r
,
A
.
G
u
z
man
,
a
n
d
K
.
A
p
a
r
i
c
i
o
,
“
M
e
n
t
a
l
h
e
a
l
t
h
i
ss
u
e
s
i
n
c
h
i
l
d
r
e
n
a
n
d
a
d
o
l
e
sce
n
t
s
w
i
t
h
c
h
r
o
n
i
c
i
l
l
n
e
ss,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
H
u
m
a
n
R
i
g
h
t
s i
n
H
e
a
l
t
h
c
a
re
,
v
o
l
.
1
0
,
n
o
.
3
,
p
p
.
1
6
3
–
1
7
3
,
2
0
1
7
,
d
o
i
:
1
0
.
1
1
0
8
/
i
j
h
r
h
-
05
-
2
0
1
7
-
0
0
2
0
.
[
4
]
W
o
r
l
d
H
e
a
l
t
h
O
r
g
a
n
i
z
a
t
i
o
n
(
W
H
O
)
,
“
D
e
p
r
e
ssi
v
e
d
i
so
r
d
e
r
(
d
e
p
r
e
ssi
o
n
)
.
”
A
c
c
e
sse
d
:
A
p
r
.
1
1
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
w
h
o
.
i
n
t
/
n
e
w
s
-
r
o
o
m/
f
a
c
t
-
sh
e
e
t
s/
d
e
t
a
i
l
/
d
e
p
r
e
ssi
o
n
[
5
]
W
o
r
l
d
H
e
a
l
t
h
O
r
g
a
n
i
z
a
t
i
o
n
(
W
H
O
)
,
“
D
e
p
r
e
ssi
o
n
a
n
d
O
t
h
e
r
C
o
mm
o
n
M
e
n
t
a
l
D
i
so
r
d
e
r
s:
G
l
o
b
a
l
H
e
a
l
t
h
Est
i
m
a
t
e
s.
”
A
c
c
e
sse
d
:
A
p
r
.
1
3
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
w
h
o
.
i
n
t
/
p
u
b
l
i
c
a
t
i
o
n
s
/
i
/
i
t
e
m/
d
e
p
r
e
ssi
o
n
-
g
l
o
b
a
l
-
he
a
l
t
h
-
e
st
i
ma
t
e
s
[
6
]
K
.
B
o
w
e
,
“
C
o
l
l
e
g
e
st
u
d
e
n
t
s
a
n
d
d
e
p
r
e
ssi
o
n
:
A
g
u
i
d
e
f
o
r
p
a
r
e
n
t
s,
”
S
p
e
a
k
i
n
g
o
f
H
e
a
l
t
h
,
M
a
y
o
C
l
i
n
i
c
H
e
a
l
t
h
S
y
st
e
ms.
A
c
c
e
sse
d
:
A
p
r
.
1
1
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
ma
y
o
c
l
i
n
i
c
h
e
a
l
t
h
sy
st
e
m.o
r
g
/
h
o
me
t
o
w
n
-
h
e
a
l
t
h
/
s
p
e
a
k
i
n
g
-
of
-
h
e
a
l
t
h
/
c
o
l
l
e
g
e
-
st
u
d
e
n
t
s
-
a
n
d
-
d
e
p
r
e
ssi
o
n
[
7
]
M
.
A
.
H
.
B
h
u
i
y
a
n
,
M
.
D
.
G
r
i
f
f
i
t
h
s
,
a
n
d
M
.
A
.
M
a
m
u
n
,
“
D
e
p
r
e
ssi
o
n
l
i
t
e
r
a
c
y
a
mo
n
g
B
a
n
g
l
a
d
e
s
h
i
p
r
e
-
u
n
i
v
e
r
si
t
y
st
u
d
e
n
t
s
:
D
i
f
f
e
r
e
n
c
e
s
b
a
se
d
o
n
g
e
n
d
e
r
,
e
d
u
c
a
t
i
o
n
a
l
a
t
t
a
i
n
me
n
t
,
d
e
p
r
e
ssi
o
n
,
a
n
d
a
n
x
i
e
t
y
,
”
Asi
a
n
J
o
u
r
n
a
l
o
f
Psy
c
h
i
a
t
ry
,
v
o
l
.
5
0
,
p
.
1
0
1
9
4
4
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
a
j
p
.
2
0
2
0
.
1
0
1
9
4
4
.
[
8
]
S
.
H
o
ssai
n
,
A
.
A
n
j
u
m,
M
.
E
.
U
d
d
i
n
,
M
.
A
.
R
a
h
ma
n
,
a
n
d
M
.
F
.
H
o
ssa
i
n
,
“
I
mp
a
c
t
s
o
f
so
c
i
o
-
c
u
l
t
u
r
a
l
e
n
v
i
r
o
n
m
e
n
t
a
n
d
l
i
f
e
st
y
l
e
f
a
c
t
o
r
s
o
n
t
h
e
p
sy
c
h
o
l
o
g
i
c
a
l
h
e
a
l
t
h
o
f
u
n
i
v
e
r
si
t
y
st
u
d
e
n
t
s
i
n
B
a
n
g
l
a
d
e
sh
:
A
l
o
n
g
i
t
u
d
i
n
a
l
s
t
u
d
y
,
”
J
o
u
rn
a
l
o
f
Af
f
e
c
t
i
v
e
D
i
s
o
r
d
e
rs
,
v
o
l
.
2
5
6
,
p
p
.
3
9
3
–
4
0
3
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
a
d
.
2
0
1
9
.
0
6
.
0
0
1
.
[
9
]
S
.
S
a
r
k
a
r
,
R
.
G
u
p
t
a
,
a
n
d
V
.
M
e
n
o
n
,
“
A
s
y
st
e
mat
i
c
r
e
v
i
e
w
o
f
d
e
p
r
e
ssi
o
n
,
a
n
x
i
e
t
y
,
a
n
d
s
t
r
e
ss
a
mo
n
g
me
d
i
c
a
l
st
u
d
e
n
t
s
i
n
I
n
d
i
a
,
”
J
o
u
rn
a
l
o
f
Me
n
t
a
l
H
e
a
l
t
h
a
n
d
H
u
m
a
n
Be
h
a
v
i
o
u
r
,
v
o
l
.
2
2
,
n
o
.
2
,
p
p
.
8
8
–
9
6
,
2
0
1
7
,
d
o
i
:
1
0
.
4
1
0
3
/
j
m
h
h
b
.
j
m
h
h
b
_
2
0
_
1
7
.
[
1
0
]
W
o
r
l
d
H
e
a
l
t
h
O
r
g
a
n
i
z
a
t
i
o
n
(
W
H
O
)
,
“
M
e
n
t
a
l
h
e
a
l
t
h
.
”
A
c
c
e
sse
d
:
A
p
r
.
1
3
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
w
h
o
.
i
n
t
/
c
h
i
n
a
/
h
e
a
l
t
h
-
t
o
p
i
c
s/
me
n
t
a
l
-
h
e
a
l
t
h
[
1
1
]
A
.
I
r
i
sh
a
n
d
N
.
S
.
M
u
r
sh
i
d
,
“
S
u
i
c
i
d
e
i
d
e
a
t
i
o
n
,
p
l
a
n
,
a
n
d
a
t
t
e
mp
t
a
mo
n
g
y
o
u
t
h
i
n
B
a
n
g
l
a
d
e
sh
:
I
n
c
i
d
e
n
c
e
a
n
d
r
i
s
k
f
a
c
t
o
r
s,
”
C
h
i
l
d
re
n
a
n
d
Y
o
u
t
h
S
e
r
v
i
c
e
s
R
e
v
i
e
w
,
v
o
l
.
1
1
6
,
p
.
1
0
5
2
1
5
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
h
i
l
d
y
o
u
t
h
.
2
0
2
0
.
1
0
5
2
1
5
.
[
1
2
]
W
o
r
l
d
H
e
a
l
t
h
O
r
g
a
n
i
z
a
t
i
o
n
(
W
H
O
)
,
“
S
u
i
c
i
d
e
,
”
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