scikit-learn/doc/modules/isotonic.rst

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.. _isotonic:
===================
Isotonic regression
===================
.. currentmodule:: sklearn.isotonic
The class :class:`IsotonicRegression` fits a non-decreasing function to data.
It solves the following problem:
minimize :math:`\sum_i w_i (y_i - \hat{y}_i)^2`
subject to :math:`\hat{y}_{min} = \hat{y}_1 \le \hat{y}_2 ... \le \hat{y}_n = \hat{y}_{max}`
where each :math:`w_i` is strictly positive and each :math:`y_i` is an
arbitrary real number. It yields the vector which is composed of non-decreasing
elements the closest in terms of mean squared error. In practice this list
of elements forms a function that is piecewise linear.
.. figure:: ../auto_examples/images/sphx_glr_plot_isotonic_regression_001.png
:target: ../auto_examples/plot_isotonic_regression.html
:align: center