Vinh Khuc created OPENNLP-671:
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Summary: Add L1-regularization into L-BFGS
Key: OPENNLP-671
URL: https://issues.apache.org/jira/browse/OPENNLP-671
Project: OpenNLP
Issue Type: Improvement
Components: Machine Learning
Reporter: Vinh Khuc
L1-regularization is useful during training Maximum Entropy models since it
pushes parameters of irrelevant features to zero. Hence, the trained model will
be sparse and compact.
When the number of features is much larger than the number of training
examples, L1 often gives better accuracy than L2.
The implementation of L1-regularization for L-BFGS will follow the method
described in the paper:
http://research.microsoft.com/en-us/um/people/jfgao/paper/icml07scalable.pdf
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