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Merge pull request #83 from ModelOriented/cran_subm
CRAN candidate
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CRAN-SUBMISSION

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Version: 0.3.4
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Date: 2023-02-25 08:41:03 UTC
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SHA: 01441b6edb0721229d98242fabe7795eaeb1af39
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Version: 0.3.5
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Date: 2023-03-31 11:06:08 UTC
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SHA: 63c092a7f51eb9eed7d88e02e38431a2bf04d0ae

DESCRIPTION

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Version: 0.3.5
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Authors@R: c(
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person("Michael", "Mayer", , "mayermichael79@gmail.com", role = c("aut", "cre")),
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person("David", "Watson", , "david.s.watson11@gmail.com", role = "ctb")
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person("David", "Watson", , "david.s.watson11@gmail.com", role = "aut"),
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person("Przemyslaw", "Biecek", , "przemyslaw.biecek@gmail.com", role = "ctb",
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comment = c(ORCID = "0000-0001-8423-1823"))
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)
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Description: Efficient implementation of Kernel SHAP, see Lundberg and Lee
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(2017) <https://dl.acm.org/doi/10.5555/3295222.3295230>, and Covert

NEWS.md

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# kernelshap 0.3.5
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## Github repository
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## Maintenance
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- New contributor: Przemyslaw Biecek - welcome on board!
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- My new cozy home: https://github.com/ModelOriented/kernelshap
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- Webpage created with "pgkdown": https://modeloriented.github.io/kernelshap
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- Webpage created with "pkgdown"
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- Introduced Github workflows
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- More unit tests
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## User visible changes
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## Small visible changes
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- Removed the `ks_extract()` function. It was designed to extract objects like the matrix `S` of SHAP values from the resulting "kernelshap" object `x`. We feel that the standard extraction options (`x$S`, `x[["S"]]`, or `getElement(x, "S")`) are sufficient.
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- Adding $(n \times K)$ matrix of predictions to the output, where $n$ is the number of rows in the explainer data `X`, and $K$ is the dimension of a single prediction (usually 1).
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## Other changes
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- More unit tests
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- Setting `verbose = FALSE` now does not suppress the warning on too large background data anymore. Use `suppressWarnings()` instead.
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# kernelshap 0.3.4
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R/kernelshap.R

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if (verbose) {
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message(txt)
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}
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if (verbose && max(m, m_exact) * bg_n > 2e5) {
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if (max(m, m_exact) * bg_n > 2e5) {
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warning("\nPredictions on large data sets with ", max(m, m_exact), "x", bg_n,
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" observations are being done. Consider reducing the computational burden ",
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"(e.g. exact = FALSE, low hybrid_degree, smaller background data, smaller m)")
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" observations are being done.\n",
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"Consider reducing the computational burden (e.g. use smaller X_bg)")
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}
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# Apply Kernel SHAP to each row of X

cran-comments.md

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Dear CRAN team
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Hello CRAN
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This is mainly a documentation update (new logo, better DESCRIPTION, better README, adding a relevant link to the description file).
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This is mainly a documentation update (new contributor, new Github repo),
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with only some small code changes (removing unnecessary function).
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## Checks
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### `check(manual = TRUE, cran = TRUE)`
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### Revdep
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── R CMD check results ──────────── kernelshap 0.3.4 ────
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Duration: 30.9s
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survex: OK
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unable to verify current time
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### `check(manual = TRUE, cran = TRUE)`
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0 errors ✔ | 0 warnings ✔ | 1 note ✖
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Note: unable to verify current time
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### `check_win_devel()`
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1 NOTE
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R Under development (unstable) (2023-02-23 r83894 ucrt)
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OK
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### `check_rhub()`
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Status: OK
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OK

packaging.R

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Otherwise, an almost exact hybrid algorithm involving iterative sampling is used.
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The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'.
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Visualizations can be done using the R package 'shapviz'.",
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`Authors@R` = "c(person('Michael', family = 'Mayer', role = c('aut', 'cre'), email = 'mayermichael79@gmail.com'),
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person('David', family = 'Watson', role = 'ctb', email = 'david.s.watson11@gmail.com'))",
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`Authors@R` =
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"c(person('Michael', family='Mayer', role=c('aut', 'cre'), email='mayermichael79@gmail.com'),
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person('David', family='Watson', role='aut', email='david.s.watson11@gmail.com'),
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person('Przemyslaw', family='Biecek', email='przemyslaw.biecek@gmail.com', role='ctb', comment=c(ORCID='0000-0001-8423-1823'))
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)",
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Depends = "R (>= 3.2.0)",
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LazyData = NULL
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),
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# Your files that do not belong to the package itself (others are added by "use_* function")
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use_build_ignore(c("^packaging.R$", "[.]Rproj$", "^compare_with_python.R$",
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"^cran-comments.md$", "^logo.png$", "^Z_exact.R$"), escape = FALSE)
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"^cran-comments.md$", "^logo.png$"), escape = FALSE)
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# If your code uses the pipe operator %>%
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# use_pipe()

revdep/README.md

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# Platform
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|field |value |
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|:--------|:----------------------------------------------------|
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|version |R version 4.2.2 (2022-10-31 ucrt) |
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|os |Windows 10 x64 (build 22621) |
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|system |x86_64, mingw32 |
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|ui |RStudio |
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|language |(EN) |
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|collate |German_Switzerland.utf8 |
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|ctype |German_Switzerland.utf8 |
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|tz |Europe/Berlin |
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|date |2023-03-31 |
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|rstudio |2022.12.0+353 Elsbeth Geranium (desktop) |
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|pandoc |2.12 @ C:\Users\Michael\anaconda3\Scripts\pandoc.exe |
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# Dependencies
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|package |old |new |Δ |
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|:----------|:------|:------|:--|
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|kernelshap |0.3.4 |0.3.5 |* |
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|foreach |1.5.2 |1.5.2 | |
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|iterators |1.0.14 |1.0.14 | |
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# Revdeps
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revdep/cran.md

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## revdepcheck results
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We checked 1 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
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* We saw 0 new problems
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* We failed to check 0 packages
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revdep/failures.md

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*Wow, no problems at all. :)*

revdep/problems.md

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*Wow, no problems at all. :)*

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