from sklearn.feature_selection import SelectFdr as SelectFdrOperation
from DashAI.back.converters.category.feature_selection import FeatureSelectionConverter
from DashAI.back.converters.sklearn_wrapper import SklearnWrapper
from DashAI.back.core.schema_fields import float_field, schema_field
from DashAI.back.core.schema_fields.base_schema import BaseSchema
class SelectFdrSchema(BaseSchema):
alpha: schema_field(
float_field(ge=0.0, le=1.0),
0.05,
"The highest uncorrected p-value for features to be kept.",
) # type: ignore
[docs]
class SelectFdr(FeatureSelectionConverter, SklearnWrapper, SelectFdrOperation):
"""SciKit-Learn's SelectFdr wrapper for DashAI."""
SCHEMA = SelectFdrSchema
DESCRIPTION = "Filter: Select features according to a false discovery rate test."
SUPERVISED = True
DISPLAY_NAME = "Select FDR"
IMAGE_PREVIEW = "select_fdr.png"
metadata = {}
[docs]
def __init__(self, **kwargs):
super().__init__(**kwargs)