updating lab version

Ch06-varselect-lab.Rmd

@@ -1,23 +1,26 @@
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+    cell_metadata_filter: language,-all
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 # Linear Models and Regularization Methods
 
-<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch06-varselect-lab.ipynb">
+<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch06-varselect-lab.ipynb">
 <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a>
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch06-varselect-lab.ipynb)
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch06-varselect-lab.ipynb)
 
 
 In this lab we implement many of the techniques discussed in this chapter.
@@ -39,7 +42,7 @@ from functools import partial
 ```
 
 We again collect the new imports
-needed for this lab. Readers will also have to have installed `l0bnb` using `pip install l0bnb`.
+needed for this lab. Readers will have installed `l0bnb` when installing the requirements.
 
 ```{python}
 from sklearn.pipeline import Pipeline
@@ -53,6 +56,14 @@ from l0bnb import fit_path
 
 ```
 
+Using `skl.ElasticNet` to fit ridge regression
+throws up many warnings. We will suppress them below by a call to `warnings.simplefilter()`.
+
+```{python}
+import warnings
+warnings.simplefilter("ignore")
+```
+
 ## Subset Selection Methods
 Here we implement methods that reduce the number of parameters in a
 model by restricting the model to a subset of the input variables.
@@ -368,7 +379,7 @@ estimates on the original scale, we must *unstandardize*
 the coefficient estimates. The parameter
 $\lambda$ in (\ref{Ch6:ridge}) and (\ref{Ch6:LASSO}) is called `alphas` in `sklearn`. In order to
 be consistent with the rest of this chapter, we use `lambdas`
-rather than `alphas` in what follows.  {At the time of publication, ridge fits like the one in code chunk [22] issue unwarranted convergence warning messages; we expect these to disappear as this package matures.}
+rather than `alphas` in what follows.  {At the time of publication, ridge fits like the one in code chunk [23] issue unwarranted convergence warning messages; we suppressed these when we filtered the warnings above.}
 
 ```{python}
 Xs = X - X.mean(0)[None,:]