Last updated: 2023-01-28

Checks: 1 1

Knit directory: multiclass_AUC/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

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The results in this page were generated with repository version b13919c. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd b13919c Ross Gayler 2023-01-26 Add notebook 04_score_dependencies
html b13919c Ross Gayler 2023-01-26 Add notebook 04_score_dependencies
Rmd 0cdb34a Ross Gayler 2023-01-24 Initial commit
html 0cdb34a Ross Gayler 2023-01-24 Initial commit

This is the website for the research project “Multiclass AUC”. See the About page for a summary description of this project.

If you have cloned the project to a local computer this website is rendered in the docs subdirectory of the project directory.

If you are using workflowr to publish the research website it will also be rendered online to GitHub Pages.

This page acts as a table of contents for the website.
There are links below to the web pages generated from the analysis notebooks.


01_read_data

Read the example datasets, calculate some check counts, reformat the data for analysis, and save to an R data file.

02_check_data

Check the ranges of the variables in the example data.

03_plot_independent_distributions

Investigate the distribution of each class score in response to cases of each class.

04_score_dependencies

Investigate the dependencies between all the class scores calculated on the same case.

05_score_calibration_1

Investigate the the scaling and calibration of the class scores (first attempt).