Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/1379#issuecomment-60792386
What is the current state of the PR? Can't see any changes in the code...
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-57055562
@jkbradley: yes, sounds great! I will give feedback to the design sheet
asap.
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GitHub user BigCrunsh opened a pull request:
https://github.com/apache/spark/pull/2398
[SPARK-3396][MLLIB] Use SquaredL2Updater in LogisticRegressionWithSGD
SimpleUpdater ignores the regularizer, which leads to an unregularized
LogReg. To enable the common L2 regularizer
Github user BigCrunsh closed the pull request at:
https://github.com/apache/spark/pull/2231
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-55594501
Changed target to master (https://github.com/apache/spark/pull/2398)
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-55261445
I have to admit that this PR may try to address too many issues at once. It
think the major ones are: Ideally,
- the model should be immutable and stateless
Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-54459193
Jenkins, retest this please.
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-54459168
@mengxr: done ;)
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Github user BigCrunsh commented on a diff in the pull request:
https://github.com/apache/spark/pull/2231#discussion_r17034656
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
---
@@ -125,4 +125,39 @@ class LogisticRegressionSuite
Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-54261292
Jenkins, test this please.
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-54271799
I am not sure why this is failing...
```
- local metrics *** FAILED ***
[info] org.apache.spark.scheduler.StageInfo@2f3ab430 fetchWaitTime
Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2231#issuecomment-54271813
Jenkins, retest this please.
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54040903
Jenkins, retest this please
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54055010
Jenkins, retest this please
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54057841
Jenkins, retest this please
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54067988
Jenkins, retest this please
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54079294
Jenkins, retest this please
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GitHub user BigCrunsh opened a pull request:
https://github.com/apache/spark/pull/2231
Use SquaredL2Updater in LogisticRegressionWithSGD
SimpleUpdater ignores the regularizer, which leads to an unregularized
LogReg. To enable the common L2 regularizer (and the corresponding
Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-54092745
@mengxr, do you agree with this modification?
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Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-53702702
@mengxr, might it be that you mistake logistic regression for Naive Bayes?
Logistic regression typically predicts well-calibrated probabilities, see e.g.
[1]; it might
Github user BigCrunsh commented on the pull request:
https://github.com/apache/spark/pull/2137#issuecomment-53569214
Currently, MLLIB contains linear models (GLMs) that produce scores based on
an inner product, classification models that might derive a classification
using scores
GitHub user BigCrunsh opened a pull request:
https://github.com/apache/spark/pull/2137
mllib: Clarify learning interfaces
** Make threshold mandatory **
Currently, the output of ``predict`` for an example is either the score
or the class. This side-effect is caused
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