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probably

Introduction

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.

Installation

You can install probably from CRAN with:

install.packages("probably")

You can install the development version of probably from GitHub with:

devtools::install_github("topepo/probably")

Examples

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.

Contributing

This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Install

install.packages('probably')

Monthly Downloads

2,382

Version

0.1.0

License

MIT + file LICENSE

Issues

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Maintainer

Max Kuhn

Last Published

August 29th, 2022

Functions in probably (0.1.0)

threshold_perf

Generate performance metrics across probability thresholds
species_probs

Predictions on animal species
segment_naive_bayes

Image segmentation predictions
reexports

Objects exported from other packages
append_class_pred

Add a class_pred column
make_class_pred

Create a class_pred vector from class probabilities
class_pred

Create a class prediction object
levels.class_pred

Extract class_pred levels
reportable_rate

Calculate the reportable rate
locate-equivocal

Locate equivocal values
as_class_pred

Coerce to a class_pred object
is_class_pred

Test if an object inherits from class_pred
probably-package

probably: Tools for Post-Processing Class Probability Estimates