Mixing
Principal Component and SVD approach
$begingroup$
Can we say PCA (principal component analysis) is the decomposite linear dependent component of matrix U and VT.
So the middle term is so-called feature extraction of the original dataset which is learning independently?
How to choose PC1 and PC2?
thanks
linear-algebra linear-programming
edited Jan 12 at 9:28
Bernard
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
$endgroup$
add a comment |
$begingroup$
Can we say PCA (principal component analysis) is the decomposite linear dependent component of matrix U and VT.
So the middle term is so-called feature extraction of the original dataset which is learning independently?
How to choose PC1 and PC2?
thanks
linear-algebra linear-programming
edited Jan 12 at 9:28
Bernard
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
$endgroup$
add a comment |
$begingroup$
Can we say PCA (principal component analysis) is the decomposite linear dependent component of matrix U and VT.
So the middle term is so-called feature extraction of the original dataset which is learning independently?
How to choose PC1 and PC2?
thanks
linear-algebra linear-programming
edited Jan 12 at 9:28
Bernard
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
$endgroup$
Can we say PCA (principal component analysis) is the decomposite linear dependent component of matrix U and VT.
So the middle term is so-called feature extraction of the original dataset which is learning independently?
How to choose PC1 and PC2?
thanks
linear-algebra linear-programming
linear-algebra linear-programming
edited Jan 12 at 9:28
Bernard
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
edited Jan 12 at 9:28
Bernard
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
edited Jan 12 at 9:28
Bernard
121k740116
edited Jan 12 at 9:28
Bernard
121k740116
edited Jan 12 at 9:28
Bernard
121k740116
121k740116
asked Jan 12 at 9:23
NewPyNewPy
11
asked Jan 12 at 9:23
NewPyNewPy
11
asked Jan 12 at 9:23
NewPyNewPy
11
11
add a comment |
add a comment |
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