High-Performance Open-Source Archive
The goal of rawKS is to easily extract the raw KS statistics to plot and report. The Python version pyks is hosted from GitHub.
The development version from GitHub with:
# install.packages("devtools")
devtools::install_github("JiaxiangBU/rawKS")library(tidyverse)
#> Registered S3 methods overwritten by 'ggplot2':
#> method from
#> [.quosures rlang
#> c.quosures rlang
#> print.quosures rlang
#> ── Attaching packages ───────────────────────────────────────────────────────── tidyverse 1.2.1 ──
#> <U+2713> ggplot2 3.1.1 <U+2713> purrr 0.3.3
#> <U+2713> tibble 2.1.3 <U+2713> dplyr 0.8.3
#> <U+2713> tidyr 0.8.3 <U+2713> stringr 1.4.0
#> <U+2713> readr 1.3.1 <U+2713> forcats 0.4.0
#> Warning: package 'purrr' was built under R version 3.6.1
#> Warning: package 'dplyr' was built under R version 3.6.1
#> ── Conflicts ──────────────────────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
library(rawKS)
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()
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