Repository: spark Updated Branches: refs/heads/master 92c0eaf34 -> 45b786aca
[MINOR][DOC] Fix wrong ml.feature.Normalizer document. ## What changes were proposed in this pull request? The ```ml.feature.Normalizer``` examples illustrate L1 norm rather than L2, we should correct corresponding document.  ## How was this patch tested? Doc change, no test. Author: Yanbo Liang <[email protected]> Closes #14787 from yanboliang/normalizer. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/45b786ac Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/45b786ac Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/45b786ac Branch: refs/heads/master Commit: 45b786aca2b5818dc233643e6b3a53b869560563 Parents: 92c0eaf Author: Yanbo Liang <[email protected]> Authored: Wed Aug 24 08:24:16 2016 -0700 Committer: Yanbo Liang <[email protected]> Committed: Wed Aug 24 08:24:16 2016 -0700 ---------------------------------------------------------------------- docs/ml-features.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/45b786ac/docs/ml-features.md ---------------------------------------------------------------------- diff --git a/docs/ml-features.md b/docs/ml-features.md index 6020114..e41bf78 100644 --- a/docs/ml-features.md +++ b/docs/ml-features.md @@ -734,7 +734,7 @@ for more details on the API. `Normalizer` is a `Transformer` which transforms a dataset of `Vector` rows, normalizing each `Vector` to have unit norm. It takes parameter `p`, which specifies the [p-norm](http://en.wikipedia.org/wiki/Norm_%28mathematics%29#p-norm) used for normalization. ($p = 2$ by default.) This normalization can help standardize your input data and improve the behavior of learning algorithms. -The following example demonstrates how to load a dataset in libsvm format and then normalize each row to have unit $L^2$ norm and unit $L^\infty$ norm. +The following example demonstrates how to load a dataset in libsvm format and then normalize each row to have unit $L^1$ norm and unit $L^\infty$ norm. <div class="codetabs"> <div data-lang="scala" markdown="1"> --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
