Last updated on 2024-05-01 12:15:12 CEST.
| Package | NOTE | OK |
|---|---|---|
| h2o4gpu | 9 | 3 |
Current CRAN status: NOTE: 9, OK: 3
Version: 0.3.3
Check: Rd files
Result: 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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