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| author | Yanbo Liang <ybliang8@gmail.com> | 2016-08-24 08:24:16 -0700 |
|---|---|---|
| committer | Yanbo Liang <ybliang8@gmail.com> | 2016-08-24 08:24:16 -0700 |
| commit | 45b786aca2b5818dc233643e6b3a53b869560563 (patch) | |
| tree | 6d5e49feb23c7f444b1dffcb8392bacf5f4bfa57 /docs | |
| parent | 92c0eaf348b42b3479610da0be761013f9d81c54 (diff) | |
| download | spark-45b786aca2b5818dc233643e6b3a53b869560563.tar.gz spark-45b786aca2b5818dc233643e6b3a53b869560563.tar.bz2 spark-45b786aca2b5818dc233643e6b3a53b869560563.zip | |
[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 <ybliang8@gmail.com>
Closes #14787 from yanboliang/normalizer.
Diffstat (limited to 'docs')
| -rw-r--r-- | docs/ml-features.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/ml-features.md b/docs/ml-features.md index 6020114845..e41bf78521 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"> |