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author | Dongjoon Hyun <dongjoon@apache.org> | 2016-06-11 12:55:38 +0100 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-06-11 12:55:38 +0100 |
commit | ad102af169c7344b30d3b84aa16452fcdc22542c (patch) | |
tree | 3ddc38bba4e271d6e361c7a880d12c030a76a532 /docs/mllib-ensembles.md | |
parent | 3761330dd0151d7369d7fba4d4c344e9863990ef (diff) | |
download | spark-ad102af169c7344b30d3b84aa16452fcdc22542c.tar.gz spark-ad102af169c7344b30d3b84aa16452fcdc22542c.tar.bz2 spark-ad102af169c7344b30d3b84aa16452fcdc22542c.zip |
[SPARK-15883][MLLIB][DOCS] Fix broken links in mllib documents
## What changes were proposed in this pull request?
This issue fixes all broken links on Spark 2.0 preview MLLib documents. Also, this contains some editorial change.
**Fix broken links**
* mllib-data-types.md
* mllib-decision-tree.md
* mllib-ensembles.md
* mllib-feature-extraction.md
* mllib-pmml-model-export.md
* mllib-statistics.md
**Fix malformed section header and scala coding style**
* mllib-linear-methods.md
**Replace indirect forward links with direct one**
* ml-classification-regression.md
## How was this patch tested?
Manual tests (with `cd docs; jekyll build`.)
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #13608 from dongjoon-hyun/SPARK-15883.
Diffstat (limited to 'docs/mllib-ensembles.md')
-rw-r--r-- | docs/mllib-ensembles.md | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/docs/mllib-ensembles.md b/docs/mllib-ensembles.md index 2416b6fa0a..5543262a89 100644 --- a/docs/mllib-ensembles.md +++ b/docs/mllib-ensembles.md @@ -9,7 +9,7 @@ displayTitle: Ensembles - spark.mllib An [ensemble method](http://en.wikipedia.org/wiki/Ensemble_learning) is a learning algorithm which creates a model composed of a set of other base models. -`spark.mllib` supports two major ensemble algorithms: [`GradientBoostedTrees`](api/scala/index.html#org.apache.spark.mllib.tree.GradientBoostedTrees) and [`RandomForest`](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest). +`spark.mllib` supports two major ensemble algorithms: [`GradientBoostedTrees`](api/scala/index.html#org.apache.spark.mllib.tree.GradientBoostedTrees) and [`RandomForest`](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest$). Both use [decision trees](mllib-decision-tree.html) as their base models. ## Gradient-Boosted Trees vs. Random Forests @@ -96,7 +96,7 @@ The test error is calculated to measure the algorithm accuracy. <div class="codetabs"> <div data-lang="scala" markdown="1"> -Refer to the [`RandomForest` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest) and [`RandomForestModel` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.model.RandomForestModel) for details on the API. +Refer to the [`RandomForest` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest$) and [`RandomForestModel` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.model.RandomForestModel) for details on the API. {% include_example scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala %} </div> @@ -127,7 +127,7 @@ The Mean Squared Error (MSE) is computed at the end to evaluate <div class="codetabs"> <div data-lang="scala" markdown="1"> -Refer to the [`RandomForest` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest) and [`RandomForestModel` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.model.RandomForestModel) for details on the API. +Refer to the [`RandomForest` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest$) and [`RandomForestModel` Scala docs](api/scala/index.html#org.apache.spark.mllib.tree.model.RandomForestModel) for details on the API. {% include_example scala/org/apache/spark/examples/mllib/RandomForestRegressionExample.scala %} </div> |