Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
warning = FALSE,
message = FALSE,
fig.width = 5,
fig.height = 4
)
## ----setup--------------------------------------------------------------------
library("ggplot2")
library("SHAPforxgboost")
library("xgboost")
set.seed(9375)
## -----------------------------------------------------------------------------
head(iris)
X <- data.matrix(iris[, -1])
dtrain <- xgb.DMatrix(X, label = iris[[1]])
fit <- xgb.train(
params = list(
objective = "reg:squarederror",
learning_rate = 0.1
),
data = dtrain,
nrounds = 50
)
## -----------------------------------------------------------------------------
# Crunch SHAP values
shap <- shap.prep(fit, X_train = X)
# SHAP importance plot
shap.plot.summary(shap)
# Alternatively, mean absolute SHAP values
shap.plot.summary(shap, kind = "bar")
# Dependence plots in decreasing order of importance
# (colored by strongest interacting variable)
for (x in shap.importance(shap, names_only = TRUE)) {
p <- shap.plot.dependence(
shap,
x = x,
color_feature = "auto",
smooth = FALSE,
jitter_width = 0.01,
alpha = 0.4
) +
ggtitle(x)
print(p)
}
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