aboutsummaryrefslogtreecommitdiff
path: root/docs/ml-clustering.md
diff options
context:
space:
mode:
authorwm624@hotmail.com <wm624@hotmail.com>2016-05-16 08:22:16 +0200
committerNick Pentreath <nickp@za.ibm.com>2016-05-16 08:22:16 +0200
commitc1836d66bdc93f80ff9e8852efe8f2d2bc1ca941 (patch)
treef690c5a5e1c2d8605acfda4876fa7a673762dc65 /docs/ml-clustering.md
parent4a5ee1954a6fb77231abb492355fe70313f0b35b (diff)
downloadspark-c1836d66bdc93f80ff9e8852efe8f2d2bc1ca941.tar.gz
spark-c1836d66bdc93f80ff9e8852efe8f2d2bc1ca941.tar.bz2
spark-c1836d66bdc93f80ff9e8852efe8f2d2bc1ca941.zip
[SPARK-15305][ML][DOC] spark.ml document Bisectiong k-means has the incorrect format
## What changes were proposed in this pull request? (Please fill in changes proposed in this fix) The generated document has the incorrect format for biseckmeans. ![bug](https://cloud.githubusercontent.com/assets/5033592/15233120/d910098a-185a-11e6-901d-44aeafc8a011.jpg) ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) Fix the formatting. ![fix](https://cloud.githubusercontent.com/assets/5033592/15233136/fce2ccd0-185a-11e6-9ded-14d71da4bdab.jpg) Author: wm624@hotmail.com <wm624@hotmail.com> Closes #13083 from wangmiao1981/doc.
Diffstat (limited to 'docs/ml-clustering.md')
-rw-r--r--docs/ml-clustering.md4
1 files changed, 1 insertions, 3 deletions
diff --git a/docs/ml-clustering.md b/docs/ml-clustering.md
index 0d69bf67df..a0955a3855 100644
--- a/docs/ml-clustering.md
+++ b/docs/ml-clustering.md
@@ -86,7 +86,6 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.clustering.
</div>
</div>
-
## Latent Dirichlet allocation (LDA)
`LDA` is implemented as an `Estimator` that supports both `EMLDAOptimizer` and `OnlineLDAOptimizer`,
@@ -116,8 +115,8 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.clustering.
{% include_example python/ml/lda_example.py %}
</div>
</div>
-## Bisecting k-means
+## Bisecting k-means
Bisecting k-means is a kind of [hierarchical clustering](https://en.wikipedia.org/wiki/Hierarchical_clustering) using a
divisive (or "top-down") approach: all observations start in one cluster, and splits are performed recursively as one
@@ -148,5 +147,4 @@ Refer to the [Python API docs](api/python/pyspark.ml.html#pyspark.ml.clustering.
{% include_example python/ml/bisecting_k_means_example.py %}
</div>
-
</div>