- XGBoost 教程
- XGBoost - 首頁
- XGBoost - 概述
- XGBoost - 架構
- XGBoost - 安裝
- XGBoost - 超引數
- XGBoost - 使用超引數調優
- XGBoost - 使用 DMatrix
- XGBoost - 分類
- XGBoost - 迴歸
- XGBoost - 正則化
- XGBoost - 學習排序
- XGBoost - 過擬合控制
- XGBoost - 分位數迴歸
- XGBoost - 自舉方法
- XGBoost - Python 實現
- XGBoost 與其他 Boosting 演算法的比較
- ZeroMQ 有用資源
- XGBoost - 有用資源
- XGBoost - 討論
XGBoost - 安裝
XGBoost 是一個改進的分散式梯度提升庫,它快速、通用且可移植。XGBoost 的安裝方法多種多樣,具體取決於作業系統和開發環境。以下是安裝 XGBoost 的不同方法。
使用 pip(適用於 Python)
安裝 XGBoost 最簡單、最常見的方法是透過 pip。因此,您只需在終端中輸入以下命令即可下載並安裝庫及其依賴項。
pip install xgboost
輸出
以下是您在終端或命令提示符中執行上述命令後的過程:
Collecting xgboost
Downloading xgboost-1.7.3-py3-none-manylinux2014_x86_64.whl (199.9 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.9/199.9 MB 8.4 MB/s eta 0:00:00
Requirement already satisfied: numpy in /usr/local/lib/python3.8/site-packages (from xgboost) (1.21.2)
Installing collected packages: xgboost
Successfully installed xgboost-1.7.3
使用 Conda(適用於 Anaconda 使用者)
如果您使用的是 Anaconda 或 Miniconda,則可以使用 Conda 安裝 XGBoost。當您執行以下命令時,它將下載所需的包和依賴項,然後將其安裝到您的系統中。
conda install -c conda-forge xgboost
輸出
終端輸出通常如下所示:
(base) $ conda install -c conda-forge xgboost
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: /path/to/conda/environment
added / updated specs:
- xgboost
The following packages will be downloaded:
package | build
------------------------------|-----------------
xgboost-1.7.3 | py38h9b699db_0 70.0 MB
------------------------------------------------------------
Total: 70.0 MB
Proceed ([y]/n)? y
Downloading and Extracting Packages
xgboost-1.7.3 | 70.0 MB | ########## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
從原始碼構建
如果您想要最新版本的 XGBoost 或想要更改您的構建,您可以透過原始碼進行。您需要在計算機上安裝 git、cmake 和其他構建工具。
首先,您需要克隆 XGBoost 儲存庫:
git clone --recursive https://github.com/dmlc/xgboost
以下是終端輸出:
$ git clone --recursive https://github.com/dmlc/xgboost Cloning into 'xgboost'... remote: Enumerating objects: 17723, done. remote: Counting objects: 100% (17723/17723), done. remote: Compressing objects: 100% (4181/4181), done. remote: Total 17723 (delta 12943), reused 16361 (delta 11547), pack-reused 0 Receiving objects: 100% (17723/17723), 28.36 MiB | 4.61 MiB/s, done. Resolving deltas: 100% (12943/12943), done.
執行上述命令後,您需要導航到克隆的目錄:
cd xgboost
現在像下面這樣構建專案:
mkdir build cd build cmake .. make -j4
終端輸出如下:
-- The CXX compiler identification is GNU 9.4.0 -- The C compiler identification is GNU 9.4.0 ... -- Configuring done -- Generating done -- Build files have been written to: /path/to/xgboost/build [ 1%] Building CXX object CMakeFiles/xgboost.dir/src/learner.cc.o [ 2%] Building CXX object CMakeFiles/xgboost.dir/src/common/host_device_vector.cc.o ... [100%] Linking CXX executable xgboost [100%] Built target xgboost
最後,安裝 python 包:
cd ../python-package python setup.py install
以下是安裝包後上述命令的輸出:
running install running bdist_egg running egg_info creating xgboost.egg-info writing xgboost.egg-info/PKG-INFO writing dependency_links to xgboost.egg-info/dependency_links.txt writing requirements to xgboost.egg-info/requires.txt writing top-level names to xgboost.egg-info/top_level.txt writing manifest file 'xgboost.egg-info/SOURCES.txt' reading manifest file 'xgboost.egg-info/SOURCES.txt' writing manifest file 'xgboost.egg-info/SOURCES.txt' installing library code to build/bdist.linux-x86_64/egg running install_lib creating /usr/local/lib/python3.8/dist-packages/xgboost-1.7.5-py3.8-linux-x86_64.egg ... byte-compiling /usr/local/lib/python3.8/dist-packages/xgboost/__init__.py to __init__.cpython-38.pyc running install_scripts creating /usr/local/bin ... running install_egg_info Writing /usr/local/lib/python3.8/dist-packages/xgboost-1.7.5-py3.8.egg-info
安裝 R 版本
如果您想使用 R 程式語言,則可以從 CRAN 儲存庫安裝 XGBoost。使用以下命令為 R 程式設計安裝它:
install.packages('catboost', repos = 'https://cloud.r-project.org/', dependencies=TRUE)
因此,該命令將為 R 程式設計安裝 CatBoost。請參考以下終端上的安裝過程輸出:
Installing package into '/home/user/R/x86_64-pc-linux-gnu-library/4.1' (as 'lib' is unspecified) trying URL 'https://cloud.r-project.org/src/contrib/xgboost_1.7.5.tar.gz' Content type 'application/x-gzip' length 2277833 bytes (2.2 MB) ================================================== downloaded 2.2 MB * installing *source* package 'xgboost' ... ** package 'xgboost' successfully unpacked and MD5 sums checked ** using staged installation ** libs *** Installing xgboost g++ -std=gnu++11 -I"/usr/share/R/include" -DNDEBUG -I../include -I../third_party/dmlc-core/include -I../third_party/rabit/include -I../third_party/xgboost/src -I../third_party/xgboost/src/../include -fpic -O2 -fPIC -c xgboost_R.cc -o xgboost_R.o ... ... ** R ** demo ** inst ** tests ** preparing package for lazy loading ** help *** installing help indices *** copying figures *** copying HTML documentation ** building package indices ** testing if installed package can be loaded * DONE (xgboost)
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