from sklearn.feature_selection import SelectPercentile as SelectPercentileOperation
from DashAI.back.converters.category.feature_selection import FeatureSelectionConverter
from DashAI.back.converters.sklearn_wrapper import SklearnWrapper
from DashAI.back.core.schema_fields import int_field, schema_field
from DashAI.back.core.schema_fields.base_schema import BaseSchema
class SelectPercentileSchema(BaseSchema):
percentile: schema_field(
int_field(ge=1, le=100),
10,
"Percent of features to keep.",
) # type: ignore
[docs]
class SelectPercentile(
FeatureSelectionConverter, SklearnWrapper, SelectPercentileOperation
):
"""SciKit-Learn's SelectPercentile wrapper for DashAI."""
SCHEMA = SelectPercentileSchema
DESCRIPTION = "Select features according to a percentile of the highest scores."
SUPERVISED = True
DISPLAY_NAME = "Select Percentile"
IMAGE_PREVIEW = "select_percentile.png"
metadata = {}
[docs]
def __init__(self, **kwargs):
if callable(self._get_tags):
original_get_tags = self._get_tags
self._get_tags = lambda *a, **k: {
**original_get_tags(*a, **k),
"requires_y": True,
}
else:
self._get_tags = {**self._get_tags, "requires_y": True}
super().__init__(**kwargs)