[MLlib][SPARK-2997] Update SVD documentation to reflect roughly square #2070
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| @@ -11,7 +11,7 @@ displayTitle: <a href="mllib-guide.html">MLlib</a> - Dimensionality Reduction | |||
| of reducing the number of variables under consideration. | |||
| It can be used to extract latent features from raw and noisy features | |||
| or compress data while maintaining the structure. | |||
| MLlib provides support for dimensionality reduction on tall-and-skinny matrices. | |||
| MLlib provides support for dimensionality reduction on the RowMatrix class. | |||
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can you add a link to the scaladoc or the documentation for RowMatrix?
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Could you give some high-level guidance on the scalability of our approaches / what sorts of matrices and values of k on which its appropriate to run MLlib's SVD?
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QA tests have started for PR 2070 at commit
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QA tests have started for PR 2070 at commit
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QA tests have finished for PR 2070 at commit
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QA tests have finished for PR 2070 at commit
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| @@ -119,14 +137,13 @@ statistical method to find a rotation such that the first coordinate has the lar | |||
| possible, and each succeeding coordinate in turn has the largest variance possible. The columns of | |||
| the rotation matrix are called principal components. PCA is used widely in dimensionality reduction. | |||
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| MLlib supports PCA for tall-and-skinny matrices stored in row-oriented format. | |||
| MLlib supports PCA for matrices stored in row-oriented format. | |||
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I think we still need tall-and-skinny matrices for PCA.
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QA tests have started for PR 2070 at commit
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QA tests have finished for PR 2070 at commit
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Aside from the one issue of |
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QA tests have started for PR 2070 at commit
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QA tests have finished for PR 2070 at commit
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I've merged this into master and branch-1.1. Thanks!! |
asfgit
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Aug 25, 2014
Update the documentation to reflect the fact we can handle roughly square matrices. Author: Reza Zadeh <rizlar@gmail.com> Closes #2070 from rezazadeh/svddocs and squashes the following commits: 826b8fe [Reza Zadeh] left singular vectors 3f34fc6 [Reza Zadeh] PCA is still TS 7ffa2aa [Reza Zadeh] better title aeaf39d [Reza Zadeh] More docs 788ed13 [Reza Zadeh] add computational cost explanation 6429c59 [Reza Zadeh] Add link to rowmatrix docs 1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square (cherry picked from commit b1b2030) Signed-off-by: Xiangrui Meng <meng@databricks.com>
xiliu82
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Sep 4, 2014
Update the documentation to reflect the fact we can handle roughly square matrices. Author: Reza Zadeh <rizlar@gmail.com> Closes apache#2070 from rezazadeh/svddocs and squashes the following commits: 826b8fe [Reza Zadeh] left singular vectors 3f34fc6 [Reza Zadeh] PCA is still TS 7ffa2aa [Reza Zadeh] better title aeaf39d [Reza Zadeh] More docs 788ed13 [Reza Zadeh] add computational cost explanation 6429c59 [Reza Zadeh] Add link to rowmatrix docs 1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square
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Update the documentation to reflect the fact we can handle roughly square matrices.