spark-calibration (homepage)

Assess binary classifier calibration (i.e., how well classifier outputs match observed class proportions) in Spark

spark-calibration is a package to to assess binary classifier calibration (i.e., how well classifier outputs match observed class proportions) in Spark.

This same code has been submitted as a pull request [PR #10666](https://github.com/apache/spark/pull/10666), so, if the PR is accepted, this code will be incorporated into Spark proper, but in the meantime, users can access the code via this little package.

Tags

  • 1|machine learning

How to

This package doesn't have any releases published in the Spark Packages repo, or with maven coordinates supplied. You may have to build this package from source, or it may simply be a script. To use this Spark Package, please follow the instructions in the README.

Releases

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