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| author | Jacek Laskowski <jacek@japila.pl> | 2016-04-02 08:12:04 -0700 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-04-02 08:12:04 -0700 |
| commit | 06694f1c68cb752ea311144f0dbe50e92e1393cf (patch) | |
| tree | 3e4de2ebd92f4909b3245f6686a400aefe56eae1 /mllib | |
| parent | 67d753516da9b6318cd4001bb7ae91703aaf098d (diff) | |
| download | spark-06694f1c68cb752ea311144f0dbe50e92e1393cf.tar.gz spark-06694f1c68cb752ea311144f0dbe50e92e1393cf.tar.bz2 spark-06694f1c68cb752ea311144f0dbe50e92e1393cf.zip | |
[MINOR] Typo fixes
## What changes were proposed in this pull request?
Typo fixes. No functional changes.
## How was this patch tested?
Built the sources and ran with samples.
Author: Jacek Laskowski <jacek@japila.pl>
Closes #11802 from jaceklaskowski/typo-fixes.
Diffstat (limited to 'mllib')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala | 2 | ||||
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala | 2 |
2 files changed, 2 insertions, 2 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala index 3a99979a88..afefaaa883 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala @@ -147,7 +147,7 @@ class Pipeline @Since("1.4.0") ( t case _ => throw new IllegalArgumentException( - s"Do not support stage $stage of type ${stage.getClass}") + s"Does not support stage $stage of type ${stage.getClass}") } if (index < indexOfLastEstimator) { curDataset = transformer.transform(curDataset) diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala index ba5ad4c072..2633c06f40 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala @@ -58,7 +58,7 @@ private[regression] trait LinearRegressionParams extends PredictorParams * The specific squared error loss function used is: * L = 1/2n ||A coefficients - y||^2^ * - * This support multiple types of regularization: + * This supports multiple types of regularization: * - none (a.k.a. ordinary least squares) * - L2 (ridge regression) * - L1 (Lasso) |