FilterFeaturesTransform

[Mr-Geekman]

🚀 Feature Request

Add FilterFeaturesTransform to filter features during transformation.

Motivation

In ensembles we want to include/exclude different features in different models. There is no way to do this on current version of the library.

Proposal

Prototype:

class _OneSegmentFilterFeaturesTransform(Transform):
    def __init__(self, include: Optional[Sequence[str]] = None, exclude: Optional[Sequence[str]] = None):
        self.include = include
        self.exclude = exclude

    def fit(self, *args) -> "_OneSegmentFilterFeaturesTransform":
        return self

    def transform(self, df: pd.DataFrame) -> pd.DataFrame:
        result = df.copy()
        if self.include is not None:
            result = result[self.include]
        if self.exclude is not None:
            result = result.drop(columns=self.exclude)
        return result


class FilterFeaturesTransform(PerSegmentWrapper):
    def __init__(self, include: Optional[Sequence[str]] = None, exclude: Optional[Sequence[str]] = None):
        self.include = include
        self.exclude = exclude

        super().__init__(
            transform=_OneSegmentFilterFeaturesTransform(
                include=self.include,
                exclude=self.exclude,
            )
        )

Test cases

1. Test that selected on and exactly one option include or exclude.
2. Test that after transform remains only features in include (test different number of features).
3. Test that after transform there are all features except for features in exclude (test different number of features).

Alternatives

No response

Additional context

No response

Checklist

• I discussed this issue with ETNA Team

[Mr-Geekman]

It is better to make it without PerSegmentWrapper.

[Mr-Geekman]

Add exception on non-existent columns and test for it.