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Hello, robust tuning parameter k should not be a constant as you
implemented.
In the paper,
http://users.stat.umn.edu/~sandy/courses/8053/handouts/robust.pdf
`k
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There is a lot of code repetition between this and #2096, perhaps you can
make the `mllib` one wrap this?
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Please add "Closes #2096" to the bottom of your PR description so the other
one gets closed when this merges.
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This class was not added by me. I didn't touch PySpark.
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Github user fjiang6 commented on the pull request:
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@dbtsai ust added the objective function, and use Params to switch between
different objective function. Thanks!
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Github user dbtsai commented on the pull request:
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Still a lot of duplication. We're adding new features into LiR now, and it
will be hard to maintain. Is it possible that you just add the objective
function, and use Para
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@mengxr @dbtsai @srowen had RobustRegression in the same LinearRegression
codebase as requested. And included the Unit Tests.
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@dbtsai @srowen had RobustRegression in the same LinearRegression codebase
as requested. And included the Unit Tests
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GitHub user fjiang6 opened a pull request:
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[SPARK-3181][MLLIB]: Add Robust Regression Algorithm with Huber Estimator
Huber Robust Regression under spark/ml/regression
Unit Tests
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@AmplabJenkins Need your help. I can build with this command:
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Github user dbtsai commented on the pull request:
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Please add the unit tests. Thanks.
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