In terminological/classifier-result:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

devtools::load_all("~/Git/tidy-info-stats/")
library(ClassifierResult)
library(standardPrintOutput)
theme_set(standardPrintOutput::defaultFigureLayout())

standard plots

devtools::load_all()
cr = ClassifierResult$fromPredictions(inr.predictions,inr.obs)

cr$plotRoc() %>% 
  standardPrintOutput::saveSixthPageFigure("~/Dropbox/classifierResult/clottingRoc")

(cr$plotDensity() + standardPrintOutput::narrowAndTall()) %>%
  standardPrintOutput::saveSixthPageFigure("~/Dropbox/classifierResult/clottingDensity")

cr$plotPR() %>% 
  standardPrintOutput::saveSixthPageFigure("~/Dropbox/classifierResult/clottingPR")

summary plot

(cr$plot() / cr$plotLegend() + patchwork::plot_layout(ncol=1, heights = c(1,0.1))) %>% 
  standardPrintOutput::saveThirdPageFigure("~/Dropbox/classifierResult/clottingSummary")

non standard plots

TODO: investigate using PMI as cost sensitive metric

cr$plotStats() %>% 
  standardPrintOutput::saveSixthPageFigure("~/Dropbox/classifierResult/clottingInfoStats")
cr$plotStats(vars(pmi_x1y1,pmi_x0y1,pmi_x1y0,pmi_x0y0,I)) %>% 
  standardPrintOutput::saveSixthPageFigure("~/Dropbox/classifierResult/clottingPmi")
cr$distributionStats() %>% tidyr::pivot_longer(everything(), names_to = "statistic", values_to = value) %>%
  standardPrintOutput::saveTable("~/Dropbox/classifierResult/clottingSummary")