fix: fmt
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//!
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//!
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//! Similar to [`PCA`](../pca/index.html), SVD is a technique that can be used to reduce the number of input variables _p_ to a smaller number _k_, while preserving
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//! Similar to [`PCA`](../pca/index.html), SVD is a technique that can be used to reduce the number of input variables _p_ to a smaller number _k_, while preserving
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//! the most important structure or relationships between the variables observed in the data.
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//! the most important structure or relationships between the variables observed in the data.
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//!
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//!
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//! Contrary to PCA, SVD does not center the data before computing the singular value decomposition.
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//! Contrary to PCA, SVD does not center the data before computing the singular value decomposition.
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//!
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//!
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//! Example:
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//! Example:
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