svn commit: r23968 - in /dev/spark/2.3.0-SNAPSHOT-2017_12_31_16_01-994065d-docs: ./ _site/ _site/api/ _site/api/R/ _site/api/java/ _site/api/java/lib/ _site/api/java/org/ _site/api/java/org/apache/ _s

2017-12-31 Thread pwendell
Author: pwendell Date: Mon Jan 1 00:14:51 2018 New Revision: 23968 Log: Apache Spark 2.3.0-SNAPSHOT-2017_12_31_16_01-994065d docs [This commit notification would consist of 1431 parts, which exceeds the limit of 50 ones, so it was shortened to the summary.]

spark git commit: [SPARK-13030][ML] Create OneHotEncoderEstimator for OneHotEncoder as Estimator

2017-12-31 Thread jkbradley
Repository: spark Updated Branches: refs/heads/master 5955a2d0f -> 994065d89 [SPARK-13030][ML] Create OneHotEncoderEstimator for OneHotEncoder as Estimator ## What changes were proposed in this pull request? This patch adds a new class `OneHotEncoderEstimator` which extends `Estimator`. The

spark git commit: [MINOR][DOCS] s/It take/It takes/g

2017-12-31 Thread srowen
Repository: spark Updated Branches: refs/heads/master 028ee4016 -> 5955a2d0f [MINOR][DOCS] s/It take/It takes/g ## What changes were proposed in this pull request? Fixing three small typos in the docs, in particular: It take a `RDD` -> It takes an `RDD` (twice) It take an `JavaRDD` -> It

svn commit: r23966 - in /dev/spark/2.3.0-SNAPSHOT-2017_12_31_08_01-028ee40-docs: ./ _site/ _site/api/ _site/api/R/ _site/api/java/ _site/api/java/lib/ _site/api/java/org/ _site/api/java/org/apache/ _s

2017-12-31 Thread pwendell
Author: pwendell Date: Sun Dec 31 16:14:45 2017 New Revision: 23966 Log: Apache Spark 2.3.0-SNAPSHOT-2017_12_31_08_01-028ee40 docs [This commit notification would consist of 1425 parts, which exceeds the limit of 50 ones, so it was shortened to the summary.]

spark git commit: [SPARK-22801][ML][PYSPARK] Allow FeatureHasher to treat numeric columns as categorical

2017-12-31 Thread mlnick
Repository: spark Updated Branches: refs/heads/master 3d8837e59 -> 028ee4016 [SPARK-22801][ML][PYSPARK] Allow FeatureHasher to treat numeric columns as categorical Previously, `FeatureHasher` always treats numeric type columns as numbers and never as categorical features. It is quite common

spark git commit: [SPARK-22397][ML] add multiple columns support to QuantileDiscretizer

2017-12-31 Thread mlnick
Repository: spark Updated Branches: refs/heads/master cfbe11e81 -> 3d8837e59 [SPARK-22397][ML] add multiple columns support to QuantileDiscretizer ## What changes were proposed in this pull request? add multi columns support to QuantileDiscretizer. When calculating the splits, we can either

svn commit: r23965 - in /dev/spark/2.3.0-SNAPSHOT-2017_12_31_00_01-cfbe11e-docs: ./ _site/ _site/api/ _site/api/R/ _site/api/java/ _site/api/java/lib/ _site/api/java/org/ _site/api/java/org/apache/ _s

2017-12-31 Thread pwendell
Author: pwendell Date: Sun Dec 31 08:16:25 2017 New Revision: 23965 Log: Apache Spark 2.3.0-SNAPSHOT-2017_12_31_00_01-cfbe11e docs [This commit notification would consist of 1425 parts, which exceeds the limit of 50 ones, so it was shortened to the summary.]