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| author | Joseph K. Bradley <joseph@databricks.com> | 2015-08-19 07:38:27 -0700 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2015-08-19 07:38:27 -0700 |
| commit | 39e4ebd521defdb68a0787bcd3bde6bc855f5198 (patch) | |
| tree | d8e7a51b1249481df3259472a225987556feb486 /docs/mllib-ensembles.md | |
| parent | 3d16a545007922ee6fa36e5f5c3959406cb46484 (diff) | |
| download | spark-39e4ebd521defdb68a0787bcd3bde6bc855f5198.tar.gz spark-39e4ebd521defdb68a0787bcd3bde6bc855f5198.tar.bz2 spark-39e4ebd521defdb68a0787bcd3bde6bc855f5198.zip | |
[SPARK-10060] [ML] [DOC] spark.ml DecisionTree user guide
New user guide section ml-decision-tree.md, including code examples.
I have run all examples, including the Java ones.
CC: manishamde yanboliang mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #8244 from jkbradley/ml-dt-docs.
Diffstat (limited to 'docs/mllib-ensembles.md')
| -rw-r--r-- | docs/mllib-ensembles.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/mllib-ensembles.md b/docs/mllib-ensembles.md index 7521fb14a7..1e00b2083e 100644 --- a/docs/mllib-ensembles.md +++ b/docs/mllib-ensembles.md @@ -9,7 +9,7 @@ displayTitle: <a href="mllib-guide.html">MLlib</a> - Ensembles 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. -MLlib supports two major ensemble algorithms: [`GradientBoostedTrees`](api/scala/index.html#org.apache.spark.mllib.tree.GradientBosotedTrees) and [`RandomForest`](api/scala/index.html#org.apache.spark.mllib.tree.RandomForest). +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 |