library("DALEX")
data(fifa)
fifa$value_eur <- fifa$value_eur/10^6
fifa[, c("nationality", "overall", "potential",
"wage_eur")] <- NULL
library("dplyr")
fifa_subset <- fifa %>%
select(matches('goalkeeping|skill'))
library("corrplot")
corrplot(cor(fifa_subset),
method = "color", type = "upper", order = "hclust",
addCoef.col = "black",number.cex = .7, diag = FALSE)
library("ranger")
set.seed(2020)
fifa_model <- ranger(value_eur~., data = fifa)
fifa_explainer <- DALEX::explain(fifa_model,
data = fifa[,-1],
y = fifa$value_eur,
label = "Random Forest",
verbose = FALSE)
library("triplot")
fifa_triplot_global <- model_triplot(fifa_explainer,
B = 1,
N = 5000,
cor_method = "pearson")
plot(fifa_triplot_global, margin_mid = 0)
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