.. _f-logreg:

module ``ml.logreg``
====================







Short summary
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module ``mlstatpy.ml.logreg``

Helpers on logistic regression.


:githublink:`%|py|5`






Functions
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+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| function                                                 | truncated documentation                                                                                                                             |
+==========================================================+=====================================================================================================================================================+
| :func:`criteria <mlstatpy.ml.logreg.criteria>`           | Computes Gini, information gain, likelihood on a dataset with two features assuming the first coordinates is used to ...                            |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`criteria2 <mlstatpy.ml.logreg.criteria2>`         | Computes Gini, information gain, likelihood on a dataset with two features assuming the first coordinates is used to ...                            |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`likelihood <mlstatpy.ml.logreg.likelihood>`       | Computes :math:`\sum_i y_i f(\theta (x_i - x_0)) + (1 - y_i) (1 - f(\theta (x_i - x_0)))` where :math:`f(x_i)` is :math:`\frac{1}{1 + e^{-x}}`. ... |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`logistic <mlstatpy.ml.logreg.logistic>`           | Computes :math:`\frac{1}{1 + e^{-x}}`.                                                                                                              |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`plog2 <mlstatpy.ml.logreg.plog2>`                 | Computes :math:`x \ln_2 x`.                                                                                                                         |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`plot_ds <mlstatpy.ml.logreg.plot_ds>`             | Plots a dataset, *X* is a dataset with two features, *y* contains the binary labels.                                                                |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+
| :func:`random_set_1d <mlstatpy.ml.logreg.random_set_1d>` | Builds a random dataset as describes in example :ref:`l-example-logistic-decision`.                                                                 |
+----------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------+








Documentation
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.. automodule:: mlstatpy.ml.logreg
    :members:
    :special-members: __init__
    :show-inheritance: