706be4e5d4
* fix rebase conflict * [core] additional gblinear improvements * [R] callback for gblinear coefficients history * force eta=1 for gblinear python tests * add top_k to GreedyFeatureSelector * set eta=1 in shotgun test * [core] fix SparsePage processing in gblinear; col-wise multithreading in greedy updater * set sorted flag within TryInitColData * gblinear tests: use scale, add external memory test * fix multiclass for greedy updater * fix whitespace * fix typo
42 lines
1.5 KiB
Plaintext
42 lines
1.5 KiB
Plaintext
Package: xgboost
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Type: Package
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Title: Extreme Gradient Boosting
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Version: 0.7.0.1
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Date: 2018-02-25
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Author: Tianqi Chen <tianqi.tchen@gmail.com>, Tong He <hetong007@gmail.com>,
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Michael Benesty <michael@benesty.fr>, Vadim Khotilovich <khotilovich@gmail.com>,
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Yuan Tang <terrytangyuan@gmail.com>
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Maintainer: Tong He <hetong007@gmail.com>
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Description: Extreme Gradient Boosting, which is an efficient implementation
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of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
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This package is its R interface. The package includes efficient linear
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model solver and tree learning algorithms. The package can automatically
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do parallel computation on a single machine which could be more than 10
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times faster than existing gradient boosting packages. It supports
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various objective functions, including regression, classification and ranking.
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The package is made to be extensible, so that users are also allowed to define
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their own objectives easily.
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License: Apache License (== 2.0) | file LICENSE
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URL: https://github.com/dmlc/xgboost
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BugReports: https://github.com/dmlc/xgboost/issues
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VignetteBuilder: knitr
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Suggests:
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knitr,
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rmarkdown,
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ggplot2 (>= 1.0.1),
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DiagrammeR (>= 0.9.0),
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Ckmeans.1d.dp (>= 3.3.1),
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vcd (>= 1.3),
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testthat,
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igraph (>= 1.0.1)
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Depends:
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R (>= 3.3.0)
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Imports:
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Matrix (>= 1.1-0),
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methods,
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data.table (>= 1.9.6),
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magrittr (>= 1.5),
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stringi (>= 0.5.2)
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RoxygenNote: 6.0.1
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SystemRequirements: GNU make, C++11
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