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kmace
kmace
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When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance (the first eigenvector is the direction in which the data varies the most, etc.); this is called principal component analysis (PCA).

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance (the first eigenvector is the direction in which the data varies the most, etc.); this is called principal component analysis (PCA).

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance (the first eigenvector is the direction in which the data varies the most, etc.); this is called principal component analysis (PCA).

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix, would they point in the direction of maximum entropy?

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amoeba
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What areis the meaning of the eigenvectors of a mutual information matrix?

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance. (the first eigenvector is the direction in which the data varies the most, etc.) [PCA]; this is called principal component analysis (PCA).

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?

What are the eigenvectors of a mutual information matrix

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance. (the first eigenvector is the direction in which the data varies the most) [PCA]

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?

What is the meaning of the eigenvectors of a mutual information matrix?

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance (the first eigenvector is the direction in which the data varies the most, etc.); this is called principal component analysis (PCA).

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?

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kmace
kmace
  • 797
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What are the eigenvectors of a mutual information matrix

When looking at the eigenvectors of the covariance matrix, we get the directions of maximum variance. (the first eigenvector is the direction in which the data varies the most) [PCA]

I was wondering what it would mean to look at the eigenvectors/values of the mutual information matrix (is there a name for this?), would they point in the direction of maximum entropy?