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Improve feature importance on GLM model

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pommedeterresautee
2015-12-01 18:44:25 +01:00
parent 423764ca2e
commit b05d5d3f24
2 changed files with 13 additions and 2 deletions
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11
R-package/tests/testthat/test_helpers.R
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@@ -15,7 +15,7 @@ df[,ID := NULL]
sparse_matrix <- sparse.model.matrix(Improved~.-1, data = df)
output_vector <- df[,Y := 0][Improved == "Marked",Y := 1][,Y]
bst <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 9,
eta = 1, nthread = 2, nround = 10,objective = "binary:logistic")
eta = 1, nthread = 2, nround = 10, objective = "binary:logistic")
feature.names <- agaricus.train$data@Dimnames[[2]]
@@ -40,6 +40,15 @@ test_that("xgb.importance works with and without feature names", {
xgb.importance(model = bst)
})
test_that("xgb.importance works with GLM model", {
bst.GLM <- xgboost(data = sparse_matrix, label = output_vector,
eta = 1, nthread = 2, nround = 10, objective = "binary:logistic", booster = "gblinear")
importance.GLM <- xgb.importance(feature_names = sparse_matrix@Dimnames[[2]], model = bst.GLM)
expect_equal(dim(importance.GLM), c(10, 2))
expect_equal(colnames(importance.GLM), c("Feature", "Weight"))
xgb.importance(model = bst.GLM)
})
test_that("xgb.plot.tree works with and without feature names", {
xgb.plot.tree(feature_names = feature.names, model = bst)
xgb.plot.tree(model = bst)