- using R Under development (unstable) (2024-12-17 r87446 ucrt)
- using platform: x86_64-w64-mingw32
- R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
- running under: Windows Server 2022 x64 (build 20348)
- using session charset: UTF-8
- checking for file 'h2o4gpu/DESCRIPTION' ... OK
- checking extension type ... Package
- this is package 'h2o4gpu' version '0.3.3'
- package encoding: UTF-8
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- checking if there is a namespace ... OK
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- checking whether package 'h2o4gpu' can be installed ... OK
See the install log for details.
- checking installed package size ... OK
- checking package directory ... OK
- checking 'build' directory ... OK
- checking DESCRIPTION meta-information ... OK
- checking top-level files ... OK
- checking for left-over files ... OK
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- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... [2s] OK
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- checking Rd files ... [1s] NOTE
checkRd: (-1) h2o4gpu.gradient_boosting_classifier.Rd:62: Lost braces; missing escapes or markup?
62 | \item{tree_method}{The tree construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
checkRd: (-1) h2o4gpu.gradient_boosting_regressor.Rd:64: Lost braces; missing escapes or markup?
64 | \item{tree_method}{The tree construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
checkRd: (-1) h2o4gpu.random_forest_classifier.Rd:58: Lost braces; missing escapes or markup?
58 | \item{tree_method}{The tree construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
checkRd: (-1) h2o4gpu.random_forest_regressor.Rd:56: Lost braces; missing escapes or markup?
56 | \item{tree_method}{The tree construction algorithm used in XGBoost Distributed and external memory version only support approximate algorithm. Choices: {‘auto’, ‘exact’, ‘approx’, ‘hist’, ‘gpu_exact’, ‘gpu_hist’} ‘auto’: Use heuristic to choose faster one. - For small to medium dataset, exact greedy will be used. - For very large-dataset, approximate algorithm will be chosen. - Because old behavior is always use exact greedy in single machine, - user will get a message when approximate algorithm is chosen to notify this choice. ‘exact’: Exact greedy algorithm. ‘approx’: Approximate greedy algorithm using sketching and histogram. ‘hist’: Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching. ‘gpu_exact’: GPU implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
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- checking examples ... [3s] OK
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- checking tests ... [39s] OK
Running 'testthat.R' [39s]
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- checking PDF version of manual ... [29s] OK
- checking HTML version of manual ... [3s] OK
- DONE
Status: 1 NOTE