[AIR] Add infrequent_categories_ attribute to OneHotEncoder and MultiHotEncoder

[bveeramani]

Description

Title.

class OneHotEncoder:
    ...
    @property
    def infrequent_categories_(self) -> list[str]:
        """Infrequent categories for each feature."""
        ...

See attributes section of https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html.

Use case

If you specify max_categories, it's not clear how you figure out which categories are dropped.

For example, suppose you have a column language with strings

language: python, java, c, python, go, ...

And you one-hot encode the dataset.

encoder = OneHotEncoder(["language"], max_features={"language": 3})
transformed_ds = encoder.fit_transform(ds)

It's not obvious which categories get dropped. One approach is to look at the column names

transformed_ds.schema().names  # ['language_python', 'language_java', 'language_c']

But it'd be nice if you could directly get which categories are dropped

encoder.infrequent_categories_  # ["go", "rust", "haskell", ...]

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