[SPARK-6332] [MLlib] compute calibration curve for binary classifiers #10666
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added 21 commits
October 5, 2015 15:40
o ProbabilisticClassifier.scala:
mention calibration in comments
o BinaryClassificationMetrics.scala:
adapting code for ROC to calibration; incomplete and commented
out for now
o BinaryClassificationMetricsSuite.scala:
tests for calibration
types to what calibration actually returns.
same as spark master again.
o ProbabilisticClassifier.scala:
mention calibration in comments
o BinaryClassificationMetrics.scala:
adapting code for ROC to calibration; incomplete and commented
out for now
o BinaryClassificationMetricsSuite.scala:
tests for calibration
types to what calibration actually returns.
same as spark master again.
…indices are not in ascending order.
string interpolation instead of pasting string together.
* replace some tuples with named variables via pattern matching * describe use of numBins parameter * revise description of return value
* break lines that are too long * remove trailing whitespace
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Can one of the admins verify this patch? |
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Thanks for the pull request. I'm going through a list of pull requests to cut them down since the sheer number is breaking some of the tooling we have. Due to lack of activity on this pull request, I'm going to push a commit to close it. Feel free to reopen it or create a new one. For this one please feel free to ping some of the committers active on ml, e.g. @jkbradley, @dbtsai, @yanboliang |
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This PR is a revised, updated version of the previous (PR #5025), which was closed for lack of activity. I have now addressed the comments about coding style, so I'd like to get the ball rolling again. I am opening a new PR as that was requested when the previous PR was closed.
The corresponding issue, SPARK-6332, is still applicable; the proposed functionality is the same as before.