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author | Dongjoon Hyun <dongjoon@apache.org> | 2016-02-22 09:52:07 +0000 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-02-22 09:52:07 +0000 |
commit | 024482bf51e8158eed08a7dc0758f585baf86e1f (patch) | |
tree | e51f2c53b027178bb4e485d2781e266d96ff6e3d /docs/mllib-clustering.md | |
parent | 1b144455b620861d8cc790d3fc69902717f14524 (diff) | |
download | spark-024482bf51e8158eed08a7dc0758f585baf86e1f.tar.gz spark-024482bf51e8158eed08a7dc0758f585baf86e1f.tar.bz2 spark-024482bf51e8158eed08a7dc0758f585baf86e1f.zip |
[MINOR][DOCS] Fix all typos in markdown files of `doc` and similar patterns in other comments
## What changes were proposed in this pull request?
This PR tries to fix all typos in all markdown files under `docs` module,
and fixes similar typos in other comments, too.
## How was the this patch tested?
manual tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #11300 from dongjoon-hyun/minor_fix_typos.
Diffstat (limited to 'docs/mllib-clustering.md')
-rw-r--r-- | docs/mllib-clustering.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md index d0be032868..8e724fbf06 100644 --- a/docs/mllib-clustering.md +++ b/docs/mllib-clustering.md @@ -300,7 +300,7 @@ for i in range(2): ## Power iteration clustering (PIC) Power iteration clustering (PIC) is a scalable and efficient algorithm for clustering vertices of a -graph given pairwise similarties as edge properties, +graph given pairwise similarities as edge properties, described in [Lin and Cohen, Power Iteration Clustering](http://www.icml2010.org/papers/387.pdf). It computes a pseudo-eigenvector of the normalized affinity matrix of the graph via [power iteration](http://en.wikipedia.org/wiki/Power_iteration) and uses it to cluster vertices. @@ -786,7 +786,7 @@ This example shows how to estimate clusters on streaming data. <div data-lang="scala" markdown="1"> Refer to the [`StreamingKMeans` Scala docs](api/scala/index.html#org.apache.spark.mllib.clustering.StreamingKMeans) for details on the API. -First we import the neccessary classes. +First we import the necessary classes. {% highlight scala %} @@ -837,7 +837,7 @@ ssc.awaitTermination() <div data-lang="python" markdown="1"> Refer to the [`StreamingKMeans` Python docs](api/python/pyspark.mllib.html#pyspark.mllib.clustering.StreamingKMeans) for more details on the API. -First we import the neccessary classes. +First we import the necessary classes. {% highlight python %} from pyspark.mllib.linalg import Vectors |