.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_gallery/3-advanced-features/plot_initial_active_set.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_gallery_3-advanced-features_plot_initial_active_set.py: Initial Active Set ================== .. GENERATED FROM PYTHON SOURCE LINES 7-17 User-specified initial active set --------------------------------- We believe that it worth allowing given an initial active set so that the splicing process starts from this set for each sparsity. It might come from prior analysis, whose result is not quite precise but better than random selection, so the algorithm can run more efficiently. Or you just want to give different initial sets to test the stability of the algorithm. Note that this is **NOT** equivalent to ``always_select``, since they can be exchanged to inactive set when splicing. To specify initial active set, an additive argument ``A_init`` should be given in ``fit()``. .. GENERATED FROM PYTHON SOURCE LINES 17-31 .. code-block:: Python import numpy as np from abess.datasets import make_glm_data from abess.linear import LinearRegression n = 100 p = 10 k = 3 np.random.seed(2) data = make_glm_data(n=n, p=p, k=k, family='gaussian') model = LinearRegression(support_size=range(0, 5), A_init=[0, 1, 2]) model.fit(data.x, data.y) .. raw:: html

LinearRegression(A_init=[0, 1, 2], support_size=range(0, 5))

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.. GENERATED FROM PYTHON SOURCE LINES 32-44 Some strategies for initial active set are: - If ``sparsity = len(A_init)``, the splicing process would start from ``A_init``. - If ``sparsity > len(A_init)``, the initial set includes ``A_init`` and other variables with larger forward sacrifices chooses. - If ``sparsity < len(A_init)``, the initial set includes part of ``A_init``. - If both ``A_init`` and ``always_select`` are given, ``always_select`` first. - For warm-start, ``A_init`` will only affect splicing under the first sparsity in ``support_size``. - For CV, ``A_init`` will affect each fold but not the re-fitting on full data. The ``abess`` R package also supports user-defined initial active set. For R tutorial, please view https://abess-team.github.io/abess/articles/v07-advancedFeatures.html. .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.003 seconds) .. _sphx_glr_download_auto_gallery_3-advanced-features_plot_initial_active_set.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_initial_active_set.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_initial_active_set.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_