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author | Yanbo Liang <ybliang8@gmail.com> | 2015-11-05 09:56:18 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-11-05 09:56:18 -0800 |
commit | 9da7ceed81b0afce7deb8f39f3a6d565d401a391 (patch) | |
tree | e6c70d2cc92cfdfd48ee366ad6230f9b87795230 /python/pyspark | |
parent | b072ff4d1d05fc212cd7036d1897a032a395f0b3 (diff) | |
download | spark-9da7ceed81b0afce7deb8f39f3a6d565d401a391.tar.gz spark-9da7ceed81b0afce7deb8f39f3a6d565d401a391.tar.bz2 spark-9da7ceed81b0afce7deb8f39f3a6d565d401a391.zip |
[SPARK-11473][ML] R-like summary statistics with intercept for OLS via normal equation solver
Follow up [SPARK-9836](https://issues.apache.org/jira/browse/SPARK-9836), we should also support summary statistics for ```intercept```.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9485 from yanboliang/spark-11473.
Diffstat (limited to 'python/pyspark')
-rw-r--r-- | python/pyspark/ml/regression.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index d7b4fd92c3..7648bf1326 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -55,15 +55,15 @@ class LinearRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPrediction >>> lr = LinearRegression(maxIter=5, regParam=0.0, solver="normal") >>> model = lr.fit(df) >>> test0 = sqlContext.createDataFrame([(Vectors.dense(-1.0),)], ["features"]) - >>> model.transform(test0).head().prediction - -1.0 - >>> model.weights - DenseVector([1.0]) - >>> model.intercept - 0.0 + >>> abs(model.transform(test0).head().prediction - (-1.0)) < 0.001 + True + >>> abs(model.coefficients[0] - 1.0) < 0.001 + True + >>> abs(model.intercept - 0.0) < 0.001 + True >>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"]) - >>> model.transform(test1).head().prediction - 1.0 + >>> abs(model.transform(test1).head().prediction - 1.0) < 0.001 + True >>> lr.setParams("vector") Traceback (most recent call last): ... |