.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "python/examples/boost_from_prediction.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_python_examples_boost_from_prediction.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_python_examples_boost_from_prediction.py:


Demo for boosting from prediction
=================================

.. GENERATED FROM PYTHON SOURCE LINES 5-36

.. code-block:: Python

    import os

    import xgboost as xgb

    CURRENT_DIR = os.path.dirname(__file__)
    dtrain = xgb.DMatrix(
        os.path.join(CURRENT_DIR, "../data/agaricus.txt.train?format=libsvm")
    )
    dtest = xgb.DMatrix(
        os.path.join(CURRENT_DIR, "../data/agaricus.txt.test?format=libsvm")
    )
    watchlist = [(dtest, "eval"), (dtrain, "train")]
    ###
    # advanced: start from a initial base prediction
    #
    print("start running example to start from a initial prediction")
    # specify parameters via map, definition are same as c++ version
    param = {"max_depth": 2, "eta": 1, "objective": "binary:logistic"}
    # train xgboost for 1 round
    bst = xgb.train(param, dtrain, 1, watchlist)
    # Note: we need the margin value instead of transformed prediction in
    # set_base_margin
    # do predict with output_margin=True, will always give you margin values
    # before logistic transformation
    ptrain = bst.predict(dtrain, output_margin=True)
    ptest = bst.predict(dtest, output_margin=True)
    dtrain.set_base_margin(ptrain)
    dtest.set_base_margin(ptest)

    print("this is result of running from initial prediction")
    bst = xgb.train(param, dtrain, 1, watchlist)


.. _sphx_glr_download_python_examples_boost_from_prediction.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: boost_from_prediction.ipynb <boost_from_prediction.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: boost_from_prediction.py <boost_from_prediction.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: boost_from_prediction.zip <boost_from_prediction.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_