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author | Dongjoon Hyun <dongjoon@apache.org> | 2016-03-04 08:25:41 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2016-03-04 08:25:41 -0800 |
commit | c8f25459ed4ad6b51a5f11665364cfe0b84f7b3c (patch) | |
tree | b055ffe282e2224a298ef7acb12bf4369d5e2475 /python/pyspark/ml/tests.py | |
parent | e617508244b508b59b4debb35cad3258cddbb9cf (diff) | |
download | spark-c8f25459ed4ad6b51a5f11665364cfe0b84f7b3c.tar.gz spark-c8f25459ed4ad6b51a5f11665364cfe0b84f7b3c.tar.bz2 spark-c8f25459ed4ad6b51a5f11665364cfe0b84f7b3c.zip |
[SPARK-13676] Fix mismatched default values for regParam in LogisticRegression
## What changes were proposed in this pull request?
The default value of regularization parameter for `LogisticRegression` algorithm is different in Scala and Python. We should provide the same value.
**Scala**
```
scala> new org.apache.spark.ml.classification.LogisticRegression().getRegParam
res0: Double = 0.0
```
**Python**
```
>>> from pyspark.ml.classification import LogisticRegression
>>> LogisticRegression().getRegParam()
0.1
```
## How was this patch tested?
manual. Check the following in `pyspark`.
```
>>> from pyspark.ml.classification import LogisticRegression
>>> LogisticRegression().getRegParam()
0.0
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #11519 from dongjoon-hyun/SPARK-13676.
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