From 16004228e75dce0a577979875506eec772dc7ba5 Mon Sep 17 00:00:00 2001 From: James Lamb Date: Mon, 6 Nov 2023 11:59:01 -0600 Subject: [PATCH] [docs] fix broken links (#6161) --- docs/.linkcheckerrc | 2 +- docs/Experiments.rst | 2 +- docs/FAQ.rst | 2 +- docs/GPU-Performance.rst | 2 +- docs/Installation-Guide.rst | 2 +- docs/Parallel-Learning-Guide.rst | 6 ------ docs/gcc-Tips.rst | 2 -- 7 files changed, 5 insertions(+), 13 deletions(-) diff --git a/docs/.linkcheckerrc b/docs/.linkcheckerrc index 96fdcbd0815..003d8699a87 100644 --- a/docs/.linkcheckerrc +++ b/docs/.linkcheckerrc @@ -11,7 +11,7 @@ ignore= http.*amd.com/.* https.*dl.acm.org/doi/.* https.*tandfonline.com/.* -ignorewarnings=http-robots-denied,https-certificate-error +ignorewarnings=http-redirected,http-robots-denied,https-certificate-error checkextern=1 [output] diff --git a/docs/Experiments.rst b/docs/Experiments.rst index ede19cf3a2e..c314321e7a3 100644 --- a/docs/Experiments.rst +++ b/docs/Experiments.rst @@ -25,7 +25,7 @@ We used 5 datasets to conduct our comparison experiments. Details of data are li +-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+ | Yahoo LTR | Learning to rank | `link `__ | 473,134 | 700 | set1.train as train, set1.test as test | +-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+ -| MS LTR | Learning to rank | `link `__ | 2,270,296 | 137 | {S1,S2,S3} as train set, {S5} as test set | +| MS LTR | Learning to rank | `link `__ | 2,270,296 | 137 | {S1,S2,S3} as train set, {S5} as test set | +-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+ | Expo | Binary classification | `link `__ | 11,000,000 | 700 | last 1,000,000 samples were used as test set | +-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+ diff --git a/docs/FAQ.rst b/docs/FAQ.rst index 3b06761114d..2e0002cb6bc 100644 --- a/docs/FAQ.rst +++ b/docs/FAQ.rst @@ -289,7 +289,7 @@ Python-package This error should be solved in latest version. If you still meet this error, try to remove ``lightgbm.egg-info`` folder in your Python-package and reinstall, -or check `this thread on stackoverflow `__. +or check `this thread on stackoverflow `__. 2. Error messages: ``Cannot ... before construct dataset``. ----------------------------------------------------------- diff --git a/docs/GPU-Performance.rst b/docs/GPU-Performance.rst index ab7ff4137cf..be1c1051bb2 100644 --- a/docs/GPU-Performance.rst +++ b/docs/GPU-Performance.rst @@ -196,7 +196,7 @@ Huan Zhang, Si Si and Cho-Jui Hsieh. `GPU Acceleration for Large-scale Tree Boos .. _link1: https://archive.ics.uci.edu/ml/datasets/HIGGS -.. _link2: http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html +.. _link2: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html .. _link3: https://www.kaggle.com/c/bosch-production-line-performance/data diff --git a/docs/Installation-Guide.rst b/docs/Installation-Guide.rst index 41f7070d6a9..1acfbcefa71 100644 --- a/docs/Installation-Guide.rst +++ b/docs/Installation-Guide.rst @@ -960,7 +960,7 @@ gcc .. _Boost Binaries: https://sourceforge.net/projects/boost/files/boost-binaries/ -.. _SWIG: http://www.swig.org/download.html +.. _SWIG: https://www.swig.org/download.html .. _this detailed guide: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html diff --git a/docs/Parallel-Learning-Guide.rst b/docs/Parallel-Learning-Guide.rst index e1857034e49..a347be94257 100644 --- a/docs/Parallel-Learning-Guide.rst +++ b/docs/Parallel-Learning-Guide.rst @@ -384,8 +384,6 @@ From the point forward, you can use any of the following methods to save the Boo Kubeflow ^^^^^^^^ -`Kubeflow Fairing`_ supports LightGBM distributed training. `These examples`_ show how to get started with LightGBM and Kubeflow Fairing in a hybrid cloud environment. - Kubeflow users can also use the `Kubeflow XGBoost Operator`_ for machine learning workflows with LightGBM. You can see `this example`_ for more details. Kubeflow integrations for LightGBM are not maintained by LightGBM's maintainers. @@ -528,10 +526,6 @@ See `the mars documentation`_ for usage examples. .. _these Dask examples: https://github.com/microsoft/lightgbm/tree/master/examples/python-guide/dask -.. _Kubeflow Fairing: https://www.kubeflow.org/docs/components/fairing/fairing-overview - -.. _These examples: https://github.com/kubeflow/fairing/tree/master/examples/lightgbm - .. _Kubeflow XGBoost Operator: https://github.com/kubeflow/xgboost-operator .. _this example: https://github.com/kubeflow/xgboost-operator/tree/master/config/samples/lightgbm-dist diff --git a/docs/gcc-Tips.rst b/docs/gcc-Tips.rst index ad5981855d2..938aee407f7 100644 --- a/docs/gcc-Tips.rst +++ b/docs/gcc-Tips.rst @@ -25,8 +25,6 @@ You can find more details on the experimentation below: - `Laurae's Benchmark Master Data (Interactive) `__ -- `Kaggle Paris Meetup #12 Slides `__ - The image below compares the runtime for training with different compiler options to a baseline using LightGBM compiled with ``-O2 --mtune=core2``. All three options are faster than that baseline. The best performance was achieved with ``-O3 --mtune=native``. .. image:: ./_static/images/gcc-comparison-2.png