probably contains tools to facilitate activities such as:
Conversion of probabilities to discrete class predictions.
Investigating and estimating optimal probability thresholds.
Inclusion of equivocal zones where the probabilities are too uncertain to report a prediction.
You can install probably from CRAN with:
You can install the development version of probably from GitHub with:
Good places to look for examples of using probably are the vignettes.
vignette("equivocal-zones", "probably") discusses the new
class_pred class that probably provides for working with equivocal zones.
vignette("where-to-use", "probably") discusses how probably fits in with the rest of the tidymodels ecosystem, and provides an example of optimizing class probability thresholds.
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For questions and discussions about tidymodels packages, modeling, and machine learning, please post on RStudio Community.
If you think you have encountered a bug, please submit an issue.
Either way, learn how to create and share a reprex (a minimal, reproducible example), to clearly communicate about your code.