.. _book_fig_chapter8_fig_rbf_ridge_mu_z:


Regularized Regression Example
------------------------------
Figure 8.4

Regularized regression for the same sample as Fig. 8.2. Here we use Gaussian
basis function regression with a Gaussian of width sigma = 0.2 centered at 100
regular intervals between 0 < z < 2. The lower panels show the best-fit weights
as a function of basis function position. The left column shows the results
with no regularization: the basis function weights w are on the order of 108,
and overfitting is evident. The middle column shows ridge regression (L2
regularization) with alpha = 0.005, and the right column shows LASSO regression
(L1 regularization) with alpha = 0.005. All three methods are fit without the
bias term (intercept).



.. image:: ../images/chapter8/fig_rbf_ridge_mu_z_1.png
    :scale: 100
    :align: center


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