Description
Interface to 'H2O4GPU' <https://github.com/h2oai/h2o4gpu>, a collection of 'GPU' solvers for machine learning algorithms.
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| r-devel-linux-x86_64-debian-gcc | NOTE |
| r-devel-linux-x86_64-fedora-clang | NOTE |
| r-devel-linux-x86_64-fedora-gcc | NOTE |
| r-devel-windows-x86_64 | NOTE |
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| r-release-windows-x86_64 | NOTE |
Check details (13 non-OK)
NOTE
r-devel-linux-x86_64-debian-clang
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-devel-linux-x86_64-debian-gcc
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-devel-linux-x86_64-fedora-clang
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-devel-linux-x86_64-fedora-gcc
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-devel-windows-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-oldrel-macos-arm64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-oldrel-macos-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-oldrel-windows-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-patched-linux-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-release-linux-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-release-macos-arm64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-release-macos-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
NOTE
r-release-windows-x86_64
Rd files
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.}
|
...[truncated]...
ee 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.}
| ^
Check History
NOTE 0 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE
r-devel-linux-x86_64-debian-clang
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-devel-linux-x86_64-debian-gcc
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-devel-linux-x86_64-fedora-clang
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-devel-linux-x86_64-fedora-gcc
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-devel-macos-arm64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-devel-windows-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-patched-linux-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-release-linux-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-release-macos-arm64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-release-macos-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-release-windows-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-oldrel-macos-arm64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-oldrel-macos-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^
NOTE
r-oldrel-windows-x86_64
Rd files
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.
...[truncated]...
U implementation of exact algorithm. ‘gpu_hist’: GPU implementation of hist algorithm.}
| ^