CRAN Package Check Results for Maintainer ‘Philipp Probst <philipp_probst at gmx.de>’

Last updated on 2024-12-22 13:49:18 CET.

Package ERROR NOTE OK
measures 8 5
OOBCurve 10 3
quantregRanger 8 5
tuneRanger 1 12
varImp 8 5

Package measures

Current CRAN status: NOTE: 8, OK: 5

Version: 0.3
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directory Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

Package OOBCurve

Current CRAN status: NOTE: 10, OK: 3

Version: 0.3
Check: dependencies in R code
Result: NOTE Namespaces in Imports field not imported from: ‘randomForest’ ‘ranger’ All declared Imports should be used. Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.3
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directory Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

Package quantregRanger

Current CRAN status: NOTE: 8, OK: 5

Version: 1.0
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directory Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

Package tuneRanger

Current CRAN status: ERROR: 1, OK: 12

Version: 0.7
Check: tests
Result: ERROR Running 'testthat.R' [33s] Running the tests in 'tests/testthat.R' failed. Complete output: > library(testthat) > library(tuneRanger) Loading required package: ranger Loading required package: mlrMBO Loading required package: mlr Loading required package: ParamHelpers Loading required package: smoof Loading required package: checkmate Loading required package: parallel Loading required package: lhs > > test_check("tuneRanger") Approximated time for tuning: 53Smtry = 2 OOB error = 0.03959951 Searching left ... mtry = 1 OOB error = 0.03581858 0.09547934 0.05 Searching right ... mtry = 4 OOB error = 0.03368273 0.05962955 0.05 mtry = 3 OOB error = 10.99107 Searching left ... mtry = 2 OOB error = 13.27389 -0.2076978 0.05 Searching right ... mtry = 6 OOB error = 12.98674 -0.1815717 0.05 mtry = 3 OOB error = 0.4414994 Searching left ... mtry = 2 OOB error = 0.4342105 0.01650943 0.05 Searching right ... mtry = 6 OOB error = 0.4110186 0.06903945 0.05 mtry = 9 OOB error = 0.4084627 0.006218333 0.05 Error: mtry can not be larger than number of variables in data. Ranger will EXIT now. [ FAIL 1 | WARN 0 | SKIP 0 | PASS 6 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_base.R:46:3'): tuneMtryFast ──────────────────────────────────── Error in `ranger(formula, data, dependent.variable.name = dependent.variable.name, mtry = res[which.min(res[, 2]), 1], ...)`: User interrupt or internal error. Backtrace: ▆ 1. └─mlr::train(learner, lung.task) at test_base.R:46:3 2. ├─mlr:::measureTime(...) 3. │ └─base::force(expr) 4. ├─base (local) fun1(...) 5. ├─base (local) fun2(fun3(do.call(trainLearner, pars))) 6. ├─base (local) fun3(do.call(trainLearner, pars)) 7. ├─base::do.call(trainLearner, pars) 8. ├─mlr (local) `<fn>`(.learner = `<srv.tnMF>`, .task = `<SurvTask>`, .subset = NULL) 9. └─tuneRanger:::trainLearner.surv.tuneMtryFast(...) 10. └─tuneRanger::tuneMtryFast(...) 11. └─ranger::ranger(...) [ FAIL 1 | WARN 0 | SKIP 0 | PASS 6 ] Error: Test failures Execution halted Flavor: r-oldrel-windows-x86_64

Package varImp

Current CRAN status: NOTE: 8, OK: 5

Version: 0.4
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directory Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.