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author | Xiangrui Meng <meng@databricks.com> | 2015-11-20 16:51:47 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-11-20 16:51:47 -0800 |
commit | a2dce22e0a25922e2052318d32f32877b7c27ec2 (patch) | |
tree | e12906b380b86a6f98230d7f4c8f74e641af8961 /docs | |
parent | 47815878ad5e47e89bfbd57acb848be2ce67a4a5 (diff) | |
download | spark-a2dce22e0a25922e2052318d32f32877b7c27ec2.tar.gz spark-a2dce22e0a25922e2052318d32f32877b7c27ec2.tar.bz2 spark-a2dce22e0a25922e2052318d32f32877b7c27ec2.zip |
Revert "[SPARK-11689][ML] Add user guide and example code for LDA under spark.ml"
This reverts commit e359d5dcf5bd300213054ebeae9fe75c4f7eb9e7.
Diffstat (limited to 'docs')
-rw-r--r-- | docs/ml-clustering.md | 30 | ||||
-rw-r--r-- | docs/ml-guide.md | 3 | ||||
-rw-r--r-- | docs/mllib-guide.md | 1 |
3 files changed, 1 insertions, 33 deletions
diff --git a/docs/ml-clustering.md b/docs/ml-clustering.md deleted file mode 100644 index 1743ef43a6..0000000000 --- a/docs/ml-clustering.md +++ /dev/null @@ -1,30 +0,0 @@ ---- -layout: global -title: Clustering - ML -displayTitle: <a href="ml-guide.html">ML</a> - Clustering ---- - -In this section, we introduce the pipeline API for [clustering in mllib](mllib-clustering.html). - -## Latent Dirichlet allocation (LDA) - -`LDA` is implemented as an `Estimator` that supports both `EMLDAOptimizer` and `OnlineLDAOptimizer`, -and generates a `LDAModel` as the base models. Expert users may cast a `LDAModel` generated by -`EMLDAOptimizer` to a `DistributedLDAModel` if needed. - -<div class="codetabs"> - -Refer to the [Scala API docs](api/scala/index.html#org.apache.spark.ml.clustering.LDA) for more details. - -<div data-lang="scala" markdown="1"> -{% include_example scala/org/apache/spark/examples/ml/LDAExample.scala %} -</div> - -<div data-lang="java" markdown="1"> - -Refer to the [Java API docs](api/java/org/apache/spark/ml/clustering/LDA.html) for more details. - -{% include_example java/org/apache/spark/examples/ml/JavaLDAExample.java %} -</div> - -</div>
\ No newline at end of file diff --git a/docs/ml-guide.md b/docs/ml-guide.md index 6f35b30c3d..be18a05361 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -40,7 +40,6 @@ Also, some algorithms have additional capabilities in the `spark.ml` API; e.g., provide class probabilities, and linear models provide model summaries. * [Feature extraction, transformation, and selection](ml-features.html) -* [Clustering](ml-clustering.html) * [Decision Trees for classification and regression](ml-decision-tree.html) * [Ensembles](ml-ensembles.html) * [Linear methods with elastic net regularization](ml-linear-methods.html) @@ -951,4 +950,4 @@ model.transform(test) {% endhighlight %} </div> -</div>
\ No newline at end of file +</div> diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index 54e35fcbb1..91e50ccfec 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -69,7 +69,6 @@ We list major functionality from both below, with links to detailed guides. concepts. It also contains sections on using algorithms within the Pipelines API, for example: * [Feature extraction, transformation, and selection](ml-features.html) -* [Clustering](ml-clustering.html) * [Decision trees for classification and regression](ml-decision-tree.html) * [Ensembles](ml-ensembles.html) * [Linear methods with elastic net regularization](ml-linear-methods.html) |