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Posted to commits@spark.apache.org by me...@apache.org on 2014/08/27 10:46:20 UTC
git commit: [SPARK-3227] [mllib] Added migration guide for v1.0 to
v1.1
Repository: spark
Updated Branches:
refs/heads/master 43dfc84f8 -> 171a41cb0
[SPARK-3227] [mllib] Added migration guide for v1.0 to v1.1
The only updates are in DecisionTree.
CC: mengxr
Author: Joseph K. Bradley <jo...@gmail.com>
Closes #2146 from jkbradley/mllib-migration and squashes the following commits:
5a1f487 [Joseph K. Bradley] small edit to doc
411d6d9 [Joseph K. Bradley] Added migration guide for v1.0 to v1.1. The only updates are in DecisionTree.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/171a41cb
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/171a41cb
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/171a41cb
Branch: refs/heads/master
Commit: 171a41cb034f4ea80f6a3c91a6872970de16a14a
Parents: 43dfc84
Author: Joseph K. Bradley <jo...@gmail.com>
Authored: Wed Aug 27 01:45:59 2014 -0700
Committer: Xiangrui Meng <me...@databricks.com>
Committed: Wed Aug 27 01:45:59 2014 -0700
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docs/mllib-guide.md | 28 +++++++++++++++++++++++++++-
1 file changed, 27 insertions(+), 1 deletion(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/171a41cb/docs/mllib-guide.md
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diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md
index d3a510b..94fc98c 100644
--- a/docs/mllib-guide.md
+++ b/docs/mllib-guide.md
@@ -60,6 +60,32 @@ To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4
# Migration Guide
+## From 1.0 to 1.1
+
+The only API changes in MLlib v1.1 are in
+[`DecisionTree`](api/scala/index.html#org.apache.spark.mllib.tree.DecisionTree),
+which continues to be an experimental API in MLlib 1.1:
+
+1. *(Breaking change)* The meaning of tree depth has been changed by 1 in order to match
+the implementations of trees in
+[scikit-learn](http://scikit-learn.org/stable/modules/classes.html#module-sklearn.tree)
+and in [rpart](http://cran.r-project.org/web/packages/rpart/index.html).
+In MLlib v1.0, a depth-1 tree had 1 leaf node, and a depth-2 tree had 1 root node and 2 leaf nodes.
+In MLlib v1.1, a depth-0 tree has 1 leaf node, and a depth-1 tree has 1 root node and 2 leaf nodes.
+This depth is specified by the `maxDepth` parameter in
+[`Strategy`](api/scala/index.html#org.apache.spark.mllib.tree.configuration.Strategy)
+or via [`DecisionTree`](api/scala/index.html#org.apache.spark.mllib.tree.DecisionTree)
+static `trainClassifier` and `trainRegressor` methods.
+
+2. *(Non-breaking change)* We recommend using the newly added `trainClassifier` and `trainRegressor`
+methods to build a [`DecisionTree`](api/scala/index.html#org.apache.spark.mllib.tree.DecisionTree),
+rather than using the old parameter class `Strategy`. These new training methods explicitly
+separate classification and regression, and they replace specialized parameter types with
+simple `String` types.
+
+Examples of the new, recommended `trainClassifier` and `trainRegressor` are given in the
+[Decision Trees Guide](mllib-decision-tree.html#examples).
+
## From 0.9 to 1.0
In MLlib v1.0, we support both dense and sparse input in a unified way, which introduces a few
@@ -85,7 +111,7 @@ val vector: Vector = Vectors.dense(array) // a dense vector
[`Vectors`](api/scala/index.html#org.apache.spark.mllib.linalg.Vectors$) provides factory methods to create sparse vectors.
-*Note*. Scala imports `scala.collection.immutable.Vector` by default, so you have to import `org.apache.spark.mllib.linalg.Vector` explicitly to use MLlib's `Vector`.
+*Note*: Scala imports `scala.collection.immutable.Vector` by default, so you have to import `org.apache.spark.mllib.linalg.Vector` explicitly to use MLlib's `Vector`.
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