8000 DOC Fix minor issues in bike sharing example by lesteve · Pull Request #21127 · scikit-learn/scikit-learn · GitHub
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DOC Fix minor issues in bike sharing example #21127

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Sep 23, 2021
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DOC Fix minor issues in bike sharing example #21127

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6 changes: 3 additions & 3 deletions examples/applications/plot_cyclical_feature_engineering.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@
# a hourly basis:
df["count"].max()

# %% [markdown]
# %%
#
# Let us rescale the target variable (number of hourly bike rentals) to predict
# a relative demand so that the mean absolute error is more easily interpreted
Expand All @@ -67,7 +67,7 @@
# intuitive than the (root) mean squared error. Note, however, that the
# best models for one metric are also the best for the other in this
# study.
y = df["count"] / 1000
y = df["count"] / df["count"].max()

# %%
fig, ax = plt.subplots(figsize=(12, 4))
Expand Down Expand Up @@ -671,7 +671,7 @@ def periodic_spline_transformer(period, n_splines=None, degree=3):
# %%
#
# We observe that this model can almost rival the performance of the gradient
# boosted trees with an average error around 6% of the maximum demand.
# boosted trees with an average error around 5% of the maximum demand.
#
# Note that while the final step of this pipeline is a linear regression model,
# the intermediate steps such as the spline feature extraction and the Nyström
Expand Down
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