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There are a couple of things that I've noticed that should be updated:
- As reported in this forum comment, we don't clarify in the instructions that at a first stage we expect students to use the whole dataset when comparing models (we later use nested cross-validation, also on the whole dataset);
- We provide the students with a list of preprocessors to evaluate:
all_preprocessors = [
None,
StandardScaler(),
MinMaxScaler(),
QuantileTransformer(n_quantiles=100),
PowerTransformer(method="box-cox"),
]
Even if it works for this small dataset, using "passthrough"
is better than using None
(I don't know if this behavior is documented somewhere in the scikit-learn doc).
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