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| author | Xiangrui Meng <meng@databricks.com> | 2014-08-19 16:06:48 -0700 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2014-08-19 16:06:48 -0700 |
| commit | 825d4fe47b9c4d48de88622dd48dcf83beb8b80a (patch) | |
| tree | d51775e9f88bff51458e57a5ec16de6e0b93b91a /docs/mllib-guide.md | |
| parent | d7e80c2597d4a9cae2e0cb35a86f7889323f4cbb (diff) | |
| download | spark-825d4fe47b9c4d48de88622dd48dcf83beb8b80a.tar.gz spark-825d4fe47b9c4d48de88622dd48dcf83beb8b80a.tar.bz2 spark-825d4fe47b9c4d48de88622dd48dcf83beb8b80a.zip | |
[SPARK-3136][MLLIB] Create Java-friendly methods in RandomRDDs
Though we don't use default argument for methods in RandomRDDs, it is still not easy for Java users to use because the output type is either `RDD[Double]` or `RDD[Vector]`. Java users should expect `JavaDoubleRDD` and `JavaRDD[Vector]`, respectively. We should create dedicated methods for Java users, and allow default arguments in Scala methods in RandomRDDs, to make life easier for both Java and Scala users. This PR also contains documentation for random data generation. brkyvz
Author: Xiangrui Meng <meng@databricks.com>
Closes #2041 from mengxr/stat-doc and squashes the following commits:
fc5eedf [Xiangrui Meng] add missing comma
ffde810 [Xiangrui Meng] address comments
aef6d07 [Xiangrui Meng] add doc for random data generation
b99d94b [Xiangrui Meng] add java-friendly methods to RandomRDDs
Diffstat (limited to 'docs/mllib-guide.md')
| -rw-r--r-- | docs/mllib-guide.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index 23d5a0c460..ca0a84a8c5 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -9,7 +9,7 @@ filtering, dimensionality reduction, as well as underlying optimization primitiv * [Data types](mllib-basics.html) * [Basic statistics](mllib-stats.html) - * data generators + * random data generation * stratified sampling * summary statistics * hypothesis testing |