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[docs] fix broken links (#6161)
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jameslamb authored Nov 6, 2023
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2 changes: 1 addition & 1 deletion docs/.linkcheckerrc
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Expand Up @@ -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]
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2 changes: 1 addition & 1 deletion docs/Experiments.rst
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Expand Up @@ -25,7 +25,7 @@ We used 5 datasets to conduct our comparison experiments. Details of data are li
+-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+
| Yahoo LTR | Learning to rank | `link <https://webscope.sandbox.yahoo.com/catalog.php?datatype=c>`__ | 473,134 | 700 | set1.train as train, set1.test as test |
+-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+
| MS LTR | Learning to rank | `link <http://research.microsoft.com/en-us/projects/mslr/>`__ | 2,270,296 | 137 | {S1,S2,S3} as train set, {S5} as test set |
| MS LTR | Learning to rank | `link <https://www.microsoft.com/en-us/research/project/mslr/>`__ | 2,270,296 | 137 | {S1,S2,S3} as train set, {S5} as test set |
+-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+
| Expo | Binary classification | `link <http://stat-computing.org/dataexpo/2009/>`__ | 11,000,000 | 700 | last 1,000,000 samples were used as test set |
+-----------+-----------------------+------------------------------------------------------------------------+-------------+----------+----------------------------------------------+
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2 changes: 1 addition & 1 deletion docs/FAQ.rst
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Expand Up @@ -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 <http://stackoverflow.com/questions/18085571/pip-install-error-setup-script-specifies-an-absolute-path>`__.
or check `this thread on stackoverflow <https://stackoverflow.com/questions/18085571/pip-install-error-setup-script-specifies-an-absolute-path>`__.

2. Error messages: ``Cannot ... before construct dataset``.
-----------------------------------------------------------
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2 changes: 1 addition & 1 deletion docs/GPU-Performance.rst
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Expand Up @@ -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

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2 changes: 1 addition & 1 deletion docs/Installation-Guide.rst
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Expand Up @@ -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

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6 changes: 0 additions & 6 deletions docs/Parallel-Learning-Guide.rst
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Expand Up @@ -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.
Expand Down Expand Up @@ -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
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2 changes: 0 additions & 2 deletions docs/gcc-Tips.rst
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Expand Up @@ -25,8 +25,6 @@ You can find more details on the experimentation below:

- `Laurae's Benchmark Master Data (Interactive) <https://public.tableau.com/views/gbt_benchmarks/Master-Data?:showVizHome=no>`__

- `Kaggle Paris Meetup #12 Slides <https://drive.google.com/file/d/0B6qJBmoIxFe0ZHNCOXdoRWMxUm8/view>`__

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
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