Xiangrui Meng created SPARK-10668:
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Summary: Use WeightedLeastSquares in LinearRegression with L2
regularization if the number of features is small
Key: SPARK-10668
URL: https://issues.apache.org/jira/browse/SPARK-10668
Project: Spark
Issue Type: New Feature
Components: ML
Reporter: Xiangrui Meng
Priority: Critical
If the number of features is small (<=4096) and the regularization is L2, we
should use WeightedLeastSquares to solve the problem rather than L-BFGS. The
former requires only one pass to the data.
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