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Easliy get TPR, FPR and KS statistic.

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JiaxiangBU/rawKS

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rawKS

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The goal of rawKS is to easily extract the raw KS statistics to plot and report. The Python version pyks is hosted from GitHub.

Installation

You can install the released version of rawKS from CRAN with:

install.packages("rawKS")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("JiaxiangBU/rawKS")

Example

This is a basic example which shows you how to solve a common problem:

library(rawKS)
#> Registered S3 methods overwritten by 'ggplot2':
#>   method         from 
#>   [.quosures     rlang
#>   c.quosures     rlang
#>   print.quosures rlang
data("two_class_example_edited")
max(ks_table(two_class_example_edited$yhat, two_class_example_edited$y)$ks)
#> [1] 0.7276892
ks_table(two_class_example_edited$yhat, two_class_example_edited$y) %>% 
  ks_plot()

Citations

Jiaxiang Li. (2020, February 8). JiaxiangBU/rawKS: rawKS 0.1.0 (Version v0.1.0). Zenodo. http://doi.org/10.5281/zenodo.3659683

@software{jiaxiang_li_2020_3659683,
  author       = {Jiaxiang Li},
  title        = {JiaxiangBU/rawKS: rawKS 0.1.0},
  month        = feb,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {v0.1.0},
  doi          = {10.5281/zenodo.3659683},
  url          = {https://doi.org/10.5281/zenodo.3659683}
}

If you use rawKS, I would be very grateful if you can add a citation in your published work. By citing rawKS, beyond acknowledging the work, you contribute to make it more visible and guarantee its growing and sustainability. For citation, please use the BibTex or the citation content.

Code of Conduct

Please note that the rawKS project is released with a Contributor Code of Conduct.
By contributing to this project, you agree to abide by its terms.

License

MIT © Jiaxiang Li

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