diff options
Diffstat (limited to 'docs/mllib-guide.md')
| -rw-r--r-- | docs/mllib-guide.md | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index 640ca83085..95ee6bc968 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -31,7 +31,7 @@ MLlib is a new component under active development. The APIs marked `Experimental`/`DeveloperApi` may change in future releases, and we will provide migration guide between releases. -## Dependencies +# Dependencies MLlib uses linear algebra packages [Breeze](http://www.scalanlp.org/), which depends on [netlib-java](https://github.com/fommil/netlib-java), and @@ -50,9 +50,9 @@ To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 --- -## Migration guide +# Migration Guide -### From 0.9 to 1.0 +## 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 breaking changes. If your data is sparse, please store it in a sparse format instead of dense to @@ -84,9 +84,9 @@ val vector: Vector = Vectors.dense(array) // a dense vector <div data-lang="java" markdown="1"> We used to represent a feature vector by `double[]`, which is replaced by -[`Vector`](api/scala/index.html#org.apache.spark.mllib.linalg.Vector) in v1.0. Algorithms that used +[`Vector`](api/java/index.html?org/apache/spark/mllib/linalg/Vector.html) in v1.0. Algorithms that used to accept `RDD<double[]>` now take -`RDD<Vector>`. [`LabeledPoint`](api/scala/index.html#org.apache.spark.mllib.regression.LabeledPoint) +`RDD<Vector>`. [`LabeledPoint`](api/java/index.html?org/apache/spark/mllib/regression/LabeledPoint.html) is now a wrapper of `(double, Vector)` instead of `(double, double[])`. Converting `double[]` to `Vector` is straightforward: |