Description Usage Arguments Examples
Variable importance is calculated as the difference between the min and max of the partial dependency output for a given feature
1 | calculate_pd_vimp(pd, vimp_colname = "ensemble")
|
pd |
output from |
vimp_colname |
name of model (taken from the column names in |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## Not run:
# Example output from calculate_partial_dependency
pd <- data.table(feature = rep("a", 9),
feature_val = rep(c(1, 3.5, 6), 3),
model = rep(c("model1",
"model2",
"ensemble"),
each = 3),
prediction = c(c(-2.5, 0, 2.5),
c(0, 0, 0),
c(-2.5, -0.75, 0)))
calculate_pd_vimp(pd, vimp_colname = "ensemble")
## End(Not run)
|
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