# Tests for package party (S4 methods)
if (require(party, quietly = TRUE)) {
# Load Friedman benchmark data
friedman1 <- readRDS("friedman.rds")$friedman1 # regression
friedman2 <- readRDS("friedman.rds")$friedman2 # classification (binary)
# Linear model; stats::lm() --------------------------------------------------
# Fit model(s)
fit1_lm <- lm(y ~ sin(pi * x.1 * x.2) + I((x.3 - 0.5)^2) + x.4 + x.5 + x.6 +
x.7 + x.8 + x.9 + x.10, data = friedman1)
fit1_glm <- glm(y ~ sin(pi * x.1 * x.2) + I((x.3 - 0.5)^2) + x.4 + x.5 + x.6 +
x.7 + x.8 + x.9 + x.10, data = friedman1)
# Partial dependence for x.3
pd1_lm <- partial(fit1_lm, pred.var = "x.3")
pd1_glm <- partial(fit1_glm, pred.var = "x.3")
# ICE curves for x.3
ice1_lm <- partial(fit1_lm, pred.var = "x.3", ice = TRUE, center = TRUE)
ice1_glm <- partial(fit1_glm, pred.var = "x.3", ice = TRUE, center = TRUE)
# Expectation(s)
expect_true(inherits(pd1_lm, what = "partial"))
expect_true(inherits(pd1_glm, what = "partial"))
expect_equal(pd1_lm, target = pd1_glm)
expect_true(inherits(ice1_lm, what = "cice"))
expect_true(inherits(ice1_glm, what = "cice"))
expect_equal(ice1_lm, target = ice1_glm)
# Display plots in a grid
grid.arrange(
plotPartial(pd1_lm),
plotPartial(pd1_glm),
plotPartial(ice1_lm),
plotPartial(ice1_glm),
nrow = 2
)
# Generalized linear model; stats::glm() -------------------------------------
# Fit model(s)
fit2_glm <- glm(y ~ sin(pi * x.1 * x.2) + I((x.3 - 0.5)^2) + x.4 + x.5 + x.6 +
x.7 + x.8 + x.9 + x.10, data = friedman2, family = binomial)
# Partial dependence for x.3
pd2_glm <- partial(fit2_glm, pred.var = "x.3")
pd2_glm_prob <- partial(fit2_glm, pred.var = "x.3", prob = TRUE)
# ICE curves for x.3
ice2_glm <- partial(fit2_glm, pred.var = "x.3", ice = TRUE, center = TRUE)
ice2_glm_prob <- partial(fit2_glm, pred.var = "x.3", prob = TRUE,
ice = TRUE, center = TRUE)
# Expectation(s)
expect_true(inherits(pd2_glm, what = "partial"))
expect_true(inherits(pd2_glm_prob, what = "partial"))
expect_true(inherits(ice2_glm, what = "cice"))
expect_true(inherits(ice2_glm_prob, what = "cice"))
# Display plots in a grid
grid.arrange(
plotPartial(pd2_glm),
plotPartial(pd2_glm_prob),
plotPartial(ice2_glm),
plotPartial(ice2_glm_prob),
nrow = 2
)
}
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