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Wolfram Language
DimensionReducers
Guides
Dimension reduction functions
Symbols
BasisVectorInterpretation
FastICA
GDCLSGlobal
GDCLS
IndependentComponentAnalysis
LeftNormalizeMatrixProduct
NearestWords
NonNegativeMatrixFactorizationGlobal
NonNegativeMatrixFactorization
NormalizeMatrixProduct
RightNormalizeMatrixProduct
AntonAntonov`DimensionReducers`
N
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Examples
(
6
)
Basic Examples
(
1
)
Create a random integer matrix:
I
n
[
1
]
:
=
S
e
e
d
R
a
n
d
o
m
[
7
]
m
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t
=
R
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d
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m
I
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g
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r
[
1
0
,
{
4
,
3
}
]
;
M
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r
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x
F
o
r
m
[
m
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]
O
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t
[
1
]
=
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m
G
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M
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:
E
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C
A
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t
a
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h
a
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h
:
-
1
7
5
7
2
2
6
8
5
8
0
3
7
0
7
1
7
7
9
O
u
t
[
1
]
/
/
M
a
t
r
i
x
F
o
r
m
=
4
7
4
1
0
8
8
5
3
4
5
4
5
Compute the NNMF factors:
I
n
[
2
]
:
=
{
W
,
H
}
=
N
o
n
N
e
g
a
t
i
v
e
M
a
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r
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x
F
a
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t
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i
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n
[
m
a
t
,
2
]
;
R
o
w
[
{
M
a
t
r
i
x
F
o
r
m
[
W
]
,
M
a
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x
F
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m
[
H
]
}
]
O
u
t
[
2
]
=
0
.
6
8
8
5
3
9
0
.
0
3
5
4
3
1
6
0
.
6
2
5
3
1
3
0
.
7
6
6
0
9
9
0
.
1
9
6
6
2
8
0
.
4
6
6
8
2
1
0
.
3
1
0
2
1
6
0
.
4
4
0
3
5
8
5
.
4
2
6
0
7
1
0
.
0
4
3
7
5
.
4
5
2
2
5
8
.
3
6
4
3
2
2
.
1
9
4
7
5
6
.
3
4
8
0
6
Here is the matrix product of the obtained factors:
I
n
[
3
]
:
=
M
a
t
r
i
x
F
o
r
m
[
W
.
H
]
O
u
t
[
3
]
/
/
M
a
t
r
i
x
F
o
r
m
=
4
.
0
3
2
4
2
6
.
9
9
3
2
5
3
.
9
7
9
0
1
9
.
8
0
0
8
9
7
.
9
6
1
8
6
8
.
2
7
2
6
4
.
9
7
1
5
5
2
.
9
9
9
4
3
4
.
0
3
5
4
7
5
.
3
6
6
5
5
4
.
0
8
2
2
4
.
4
8
6
7
9
Note that elementwise relative errors between the original matrix and reconstructed matrix are small:
I
n
[
4
]
:
=
M
a
t
r
i
x
F
o
r
m
[
R
o
u
n
d
[
(
W
.
H
-
m
a
t
)
/
m
a
t
,
0
.
0
0
1
]
]
O
u
t
[
4
]
/
/
M
a
t
r
i
x
F
o
r
m
=
0
.
0
0
8
-
0
.
0
0
1
-
0
.
0
0
5
-
0
.
0
2
-
0
.
0
0
5
0
.
0
3
4
-
0
.
0
0
6
0
.
0
.
0
0
9
0
.
0
7
3
0
.
0
2
1
-
0
.
1
0
3
S
c
o
p
e
(
1
)
O
p
t
i
o
n
s
(
2
)
A
p
p
l
i
c
a
t
i
o
n
s
(
1
)
P
r
o
p
e
r
t
i
e
s
&
R
e
l
a
t
i
o
n
s
(
1
)
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