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    <p>XGBoost is a specific implementation of gradient boosting trees,
      so strictly speaking scikit-learn cannot "contain" XGBoost. That
      being said:
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    <p>- XGBoost has a scikit-learn compatible API:
<a class="moz-txt-link-freetext" href="https://xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.sklearn">https://xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.sklearn</a>.
      So does LightGBM, another fast implementation of gradient boosting
      trees.<br>
    </p>
    <p>- scikit-learn implements "vanilla" gradient boosting
      <a class="moz-txt-link-freetext" href="https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting">https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting</a><br>
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    <p>- There's an open PR in scikit learn (still very WIP) that
      implements the same kind of optimization that XGBoost and LightGBM
      use, which will make GBDT faster
      <a class="moz-txt-link-freetext" href="https://github.com/scikit-learn/scikit-learn/pull/12807">https://github.com/scikit-learn/scikit-learn/pull/12807</a>.<br>
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    <div class="moz-cite-prefix">Nicolas</div>
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    <div class="moz-cite-prefix">On 1/8/19 8:23 PM, lampahome wrote:<br>
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    <blockquote type="cite"
cite="mid:CAB3eZftOCBanfJ4sAY2p4vV74ecB3=atD+fzzSZiTTxO2Uje-w@mail.gmail.com">
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      <div dir="ltr">As title
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        <div>Does sklearn contain xgboost to use? </div>
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        <div>thanks</div>
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      <pre class="moz-quote-pre" wrap="">_______________________________________________
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