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 <joseph.kurata.brad...@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 <joseph.kurata.brad...@gmail.com> Authored: Wed Aug 27 01:45:59 2014 -0700 Committer: Xiangrui Meng <m...@databricks.com> Committed: Wed Aug 27 01:45:59 2014 -0700 ---------------------------------------------------------------------- docs/mllib-guide.md | 28 +++++++++++++++++++++++++++- 1 file changed, 27 insertions(+), 1 deletion(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/171a41cb/docs/mllib-guide.md ---------------------------------------------------------------------- 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`. </div> --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
