Facundo Bellosi created SPARK-26173:
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Summary: Prior regularization for Logistic Regression
Key: SPARK-26173
URL: https://issues.apache.org/jira/browse/SPARK-26173
Project: Spark
Issue Type: New Feature
Components: MLlib
Affects Versions: 2.4.0
Reporter: Facundo Bellosi
This feature enables Maximum A Posteriori (MAP) optimization for Logistic
Regression based on a Gaussian prior. In practice, this is just implementing a
more general form of L2 regularization parameterized by a (multivariate) mean
and precisions vectors. Prior Regularization is enabled when both vectors are
provided and regParam > 0 and elasticNetParam < 1.
Reference: Bishop, Christopher M. (2006). _Pattern Recognition and Machine
Learning_ (section 4.5). Berlin, Heidelberg: Springer-Verlag.
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