[SPARK-17239][ML][DOC] Update user guide for multiclass logistic regression #15349
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sethah
commented
Oct 4, 2016
| @@ -45,6 +45,19 @@ object LogisticRegressionWithElasticNetExample { | |||
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| // Print the coefficients and intercept for logistic regression | |||
| println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}") | |||
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I modified the existing examples to show that multinomial can be used with binary classification. It might be too confusing, but then that might be more reason to have some example to clarify it. I appreciate feedback here.
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Test build #66332 has finished for PR 15349 at commit
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LGTM. Merged into master. Thanks. |
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Thanks @dbtsai! |
uzadude
pushed a commit
to uzadude/spark
that referenced
this pull request
Jan 27, 2017
…ession ## What changes were proposed in this pull request? Updates user guide to reflect that LogisticRegression now supports multiclass. Also adds new examples to show multiclass training. ## How was this patch tested? Ran locally using spark-submit, run-example, and copy/paste from user guide into shells. Generated docs and verified correct output. Author: sethah <seth.hendrickson16@gmail.com> Closes apache#15349 from sethah/SPARK-17239.
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What changes were proposed in this pull request?
Updates user guide to reflect that LogisticRegression now supports multiclass. Also adds new examples to show multiclass training.
How was this patch tested?
Ran locally using spark-submit, run-example, and copy/paste from user guide into shells. Generated docs and verified correct output.