Seth Hendrickson created SPARK-18456:
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Summary: Use matrix abstraction for LogisitRegression coefficients
during training
Key: SPARK-18456
URL: https://issues.apache.org/jira/browse/SPARK-18456
Project: Spark
Issue Type: Improvement
Components: ML
Reporter: Seth Hendrickson
Priority: Minor
This is a follow up from
[SPARK-18060|https://issues.apache.org/jira/browse/SPARK-18060]. The current
code for logistic regression relies on manually indexing flat arrays of column
major coefficients, which can be messy and is hard to maintain. We can use a
matrix abstraction instead of a flat array to simplify things. This will make
the code easier to read and maintain.
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