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Merge pull request #32 from kapsner/master
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Added orcid to description file.
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krzyzinskim authored Oct 4, 2023
2 parents 5ee819f + 1cf7dc1 commit 25b8238
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12 changes: 6 additions & 6 deletions DESCRIPTION
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Package: treeshap
Title: Compute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP'
Algorithm
Version: 0.2.5.9000
Version: 0.2.5.9001
Authors@R: c(
person("Konrad", "Komisarczyk", , "komisarczykkonrad@gmail.com", role = "aut"),
person("Pawel", "Kozminski", , "pkozminski99@gmail.com", role = "aut"),
person("Konrad", "Komisarczyk", email = "komisarczykkonrad@gmail.com", role = "aut"),
person("Pawel", "Kozminski", email = "pkozminski99@gmail.com", role = "aut"),
person("Szymon", "Maksymiuk", role = "aut"),
person("Lorenz A.", "Kapsner", role = "ctb"),
person("Lorenz A.", "Kapsner", role = "ctb", comment = c(ORCID = "0000-0003-1866-860X")),
person("Mikolaj", "Spytek", role = "ctb"),
person("Mateusz", "Krzyzinski", , "krzyzinskimateusz23@gmail.com", role = c("ctb", "cre")),
person("Przemyslaw", "Biecek", , "przemyslaw.biecek@gmail.com", role = c("aut", "cph"))
person("Mateusz", "Krzyzinski", email = "krzyzinskimateusz23@gmail.com", role = c("ctb", "cre")),
person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cph"))
)
Description: An efficient implementation of the 'TreeSHAP' algorithm
introduced by Lundberg et al., (2020) <doi:10.1038/s42256-019-0138-9>.
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1 change: 0 additions & 1 deletion R/unify_ranger_surv.R
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#' unified_model_risk <- ranger_surv.unify(rf, train_x, type = "risk")
#' shaps <- treeshap(unified_model_risk, train_x[1:2,])
#'
#'
#' # compute shaps for 3 selected time points
#' unified_model_surv <- ranger_surv.unify(rf, train_x, type = "survival", times = c(23, 50, 73))
#' for (i in 1:3) {
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1 change: 0 additions & 1 deletion man/ranger_surv.unify.Rd

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1 change: 0 additions & 1 deletion tests/testthat/test_ranger_surv.R
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Expand Up @@ -165,7 +165,6 @@ test_that('ranger_surv.unify (type = "survival"): mean prediction calculated usi

#expect_true(all(abs((intercept_predict - intercept_covers) / intercept_predict) < 10**(-14)))
expect_equal(intercept_predict, intercept_covers)

})

test_that('ranger_surv.unify (type = "survival"): covers correctness', {
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