detect.binarizer package

Submodules

• detect.binarizer.Binarizer module
  • Bin
    • Bin.evaluate()
    • Bin.negate_self()
  • Binarizer
    • Binarizer.data_handler
    • Binarizer.encode()
    • Binarizer.encode_y()
    • Binarizer.feature_names()
    • Binarizer.get_bin_encodings()
    • Binarizer.multi_index_feats()
    • Binarizer.target_name()
  • Operation
    • Operation.BETWEEN
    • Operation.EQ
    • Operation.GE
    • Operation.GT
    • Operation.IN
    • Operation.LE
    • Operation.LT
    • Operation.NE
    • Operation.NOT_IN
    • Operation.OUTSIDE
    • Operation.negated()
    • Operation.perform()

Module contents

class detect.binarizer.Bin(feature: Feature, operation: Operation, value: float | tuple[float, float] | int | str | list[int | str] | bool)

Bases: object

evaluate(values: ndarray[int | float | str]) → ndarray[bool]

negate_self()

class detect.binarizer.Binarizer(data_handler: DataHandler, target_positive_vals: list[int | str] | None = None)

Bases: object

Handles binarizing the dataset

property data_handler

encode(X: ndarray | DataFrame, include_negations=False, include_binary_negations=False) → ndarray[bool]

encode_y(y: ndarray | Series) → ndarray[bool]

feature_names(include_negations=False, include_binary_negations=False) → list[str]

get_bin_encodings(include_negations=False, include_binary_negations=False, return_flat=True)

multi_index_feats(include_negations=False, include_binary_negations=False) → MultiIndex

target_name() → tuple[str, str]

class detect.binarizer.Operation(value)

Bases: Enum

BETWEEN = 'between'

EQ = '='

GE = '>='

GT = '>'

IN = 'in'

LE = '<='

LT = '<'

NE = '!='

NOT_IN = 'not in'

OUTSIDE = 'outside'

classmethod negated(op) → Operation

classmethod perform(op: Operation, vals: ndarray[int | float | str], reference: float | tuple[float, float] | int | str | list[int | str] | bool) → ndarray[bool]