[SPARK-19762][ML][FOLLOWUP]Add necessary comments to L2Regularization. #18992
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@sethah @srowen Thanks for your great contributions of #17094. I wish you would not mind, I found these annotation section was missing. I think these are very important to let users/developers to understand how we handle standardization, so I add them back. Would you mind to have a look? Thanks. cc @MLnick @WeichenXu123 |
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Test build #80839 has finished for PR 18992 at commit
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WeichenXu123
approved these changes
Aug 20, 2017
| // to improve the rate of convergence; as a result, we have to | ||
| // perform this reverse standardization by penalizing each component | ||
| // differently to get effectively the same objective function when | ||
| // the training dataset is not standardized. |
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Yes this is an important comment we need keep.
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Merged into master. Thanks. |
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What changes were proposed in this pull request?
MLlib
LinearRegression/LogisticRegression/LinearSVCalways standardize the data during training to improve the rate of convergence regardless of standardization is true or false. If standardization is false, we perform reverse standardization by penalizing each component differently to get effectively the same objective function when the training dataset is not standardized. We should keep these comments in the code to let developers understand how we handle it correctly.How was this patch tested?
Existing tests, only adding some comments in code.