V2.1rc (#4)
* change to README * update README * frozen versions for v2 * frozen requirements, ISLP==0.3.19 * v2.1 notebooks excluding 10,13 * v2.1 of Ch13 * pairing notebooks * v2.1 of Ch10 * update README for v2.1 * update README * remove workflows: notebooks can be tested in ISLP
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@@ -83,7 +83,7 @@ for feature transformations such as `PCA()` seen in Section 6.5.3) which
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allows for easy evaluation of the polynomial at new data points. Here `poly()` is referred to as a *helper* function, and sets up the transformation; `Poly()` is the actual workhorse that computes the transformation. See also
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the
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discussion of transformations on
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page 127.
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page 129.
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In the code above, the first line executes the `fit()` method
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using the dataframe
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@@ -748,7 +748,6 @@ ANOVA, $\mathcal{M}_2$ is preferred.
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We can repeat the same process for `age` as well. We see there is very clear evidence that
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a non-linear term is required for `age`.
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\newpage
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```{python}
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gam_0 = LinearGAM(year_term +
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