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Add SHAP summary plot using ggplot2 (#5882)

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* add SHAP summary plot using ggplot2

* Update xgb.plot.shap

* Update example in xgb.plot.shap documentation

* update logic, add tests

* whitespace fixes

* whitespace fixes for test_helpers

* namespace for sd function

* explicitly declare variables that are automatically evaluated by data.table

* Fix R lint

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Cuong Duong
2020-08-19 11:04:09 +10:00
committed by GitHub
parent 989ddd036f
commit e51cba6195
3 changed files with 238 additions and 55 deletions
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40
R-package/tests/testthat/test_helpers.R
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@@ -351,11 +351,47 @@ test_that("xgb.plot.deepness works", {
xgb.ggplot.deepness(model = bst.Tree)
})
test_that("xgb.shap.data works when top_n is provided", {
data_list <- xgb.shap.data(data = sparse_matrix, model = bst.Tree, top_n = 2)
expect_equal(names(data_list), c("data", "shap_contrib"))
expect_equal(NCOL(data_list$data), 2)
expect_equal(NCOL(data_list$shap_contrib), 2)
expect_equal(NROW(data_list$data), NROW(data_list$shap_contrib))
expect_gt(length(colnames(data_list$data)), 0)
expect_gt(length(colnames(data_list$shap_contrib)), 0)
# for multiclass without target class provided
data_list <- xgb.shap.data(data = as.matrix(iris[, -5]), model = mbst.Tree, top_n = 2)
expect_equal(dim(data_list$shap_contrib), c(nrow(iris), 2))
# for multiclass with target class provided
data_list <- xgb.shap.data(data = as.matrix(iris[, -5]), model = mbst.Tree, top_n = 2, target_class = 0)
expect_equal(dim(data_list$shap_contrib), c(nrow(iris), 2))
})
test_that("xgb.shap.data works with subsampling", {
data_list <- xgb.shap.data(data = sparse_matrix, model = bst.Tree, top_n = 2, subsample = 0.8)
expect_equal(NROW(data_list$data), as.integer(0.8 * nrow(sparse_matrix)))
expect_equal(NROW(data_list$data), NROW(data_list$shap_contrib))
})
test_that("prepare.ggplot.shap.data works", {
data_list <- xgb.shap.data(data = sparse_matrix, model = bst.Tree, top_n = 2)
plot_data <- prepare.ggplot.shap.data(data_list, normalize = TRUE)
expect_s3_class(plot_data, "data.frame")
expect_equal(names(plot_data), c("id", "feature", "feature_value", "shap_value"))
expect_s3_class(plot_data$feature, "factor")
# Each observation should have 1 row for each feature
expect_equal(nrow(plot_data), nrow(sparse_matrix) * 2)
})
test_that("xgb.plot.shap works", {
sh <- xgb.plot.shap(data = sparse_matrix, model = bst.Tree, top_n = 2, col = 4)
expect_equal(names(sh), c("data", "shap_contrib"))
expect_equal(NCOL(sh$data), 2)
expect_equal(NCOL(sh$shap_contrib), 2)
})
test_that("xgb.plot.shap.summary works", {
xgb.plot.shap.summary(data = sparse_matrix, model = bst.Tree, top_n = 2)
xgb.ggplot.shap.summary(data = sparse_matrix, model = bst.Tree, top_n = 2)
})
test_that("check.deprecation works", {