tests/testthat.R

In mstaniak/egalitaRian: Compare Validation and Training Datasets and Explore Differences

library(testthat)
library(dplyr)
library(egalitaRian)
library(mlr)
library(live)
library(lime)

requireNamespace("MASS", quietly = TRUE)

set.seed(17)
training_dataset <- as.data.frame(MASS::mvrnorm(n = 100, mu = rep(0, 20), Sigma = diag(1, 20)))
training_dataset$fct <- as.factor(as.character(rbinom(100, size = 5, prob = 0.4)))
set.seed(19)
validation_dataset <- as.data.frame(MASS::mvrnorm(n = 50, mu = rep(0, 20), Sigma = diag(5, 20)))
validation_dataset$fct <- as.factor(as.character(rbinom(50, size = 5, prob = 0.4)))

set.seed(17)
training_dataset$y <- as.factor(
  ifelse(rowSums(training_dataset[, 1:20])^2 + (training_dataset$fct == 2) > 2,
         "good", "bad"))
validation_dataset$y <- as.factor(
  ifelse(rowSums(validation_dataset[, 1:20])^2 + (validation_dataset$fct == 2) > 2,
         "good", "bad"))

regr_glm <- glm(y ~., data = training_dataset, family = "binomial")

egalitarian_explanation <- egalitarian(training_dataset,
                                       validation_dataset,
                                       target = "y",
                                       model = regr_glm)

test_check("egalitaRian")