CONTRIBUTING.md
In mfrasco/Metrics: Evaluation Metrics for Machine Learning
Contributing to Metrics
Contributions from the open source community--especially first time contributors--are welcome and encouraged. Thank you for taking an interest in this project.
If you have a question about the package or an idea for the package
You should open up a new issue that describes your question or your idea. Be sure to look through the existing issues.
You can ask questions about how a function works, about the documentation for a function, or about the package in general. If you have an idea for a new metric function that can be added to the package, be sure to describe how the metric is used.
What to do if you found a bug
You should open up a new issue that provides a reproducible example of the bug. If you've never heard of a reproducible example (or reprex) before, you can read about them here. The goal of a reprex is to make it as easy as possible for me to recreate your problem so that I can fix it.
What to do if you've fixed a bug or added a new feature
If this is your first contribution to an open source project, I recommend that you read this.
Otherwise, please make the pull request from your forked repo against the master branch of this repo.
mfrasco/Metrics documentation built on May 13, 2019, 12:31 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Contributing to Metrics
Contributions from the open source community--especially first time contributors--are welcome and encouraged. Thank you for taking an interest in this project.
If you have a question about the package or an idea for the package
You should open up a new issue that describes your question or your idea. Be sure to look through the existing issues.
You can ask questions about how a function works, about the documentation for a function, or about the package in general. If you have an idea for a new metric function that can be added to the package, be sure to describe how the metric is used.
What to do if you found a bug
You should open up a new issue that provides a reproducible example of the bug. If you've never heard of a reproducible example (or reprex) before, you can read about them here. The goal of a reprex is to make it as easy as possible for me to recreate your problem so that I can fix it.
What to do if you've fixed a bug or added a new feature
If this is your first contribution to an open source project, I recommend that you read this.
Otherwise, please make the pull request from your forked repo against the master branch of this repo.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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