`CUSUM`#

class capymoa.drift.detectors.CUSUM[source]#

Bases: MOADriftDetector

CUSUM Drift Detector

Example usages:

>>> import numpy as np
>>> np.random.seed(0)
>>> from capymoa.drift.detectors import CUSUM
>>>
>>> detector = CUSUM(delta=0.005, lambda_=60)
>>>
>>> data_stream = np.random.randint(2, size=2000)
>>> for i in range(999, 2000):
...     data_stream[i] = np.random.randint(4, high=8)
>>>
>>> for i in range(2000):
...     detector.add_element(data_stream[i])
...     if detector.detected_change():
...         print('Change detected in data: ' + str(data_stream[i]) + ' - at index: ' + str(i))
Change detected in data: 6 - at index: 1011
Change detected in data: 7 - at index: 1556

__init__(min_n_instances: int = 30, delta: float = 0.005, lambda_: float = 50)[source]#

Create a CUSUM drift detector.

Parameters:

min_n_instances – Minimum number of instances to observe before change detection is enabled. Defaults to 30.
delta – CUSUM slack parameter subtracted from the running sum at each step. Larger values make the detector less sensitive to small shifts. Defaults to 0.005.
lambda – Threshold for the cumulative sum; once the running sum exceeds this value, a change is reported. Defaults to 50.

add_element(element: float) → None[source]#

Update the drift detector with a new input value.

Parameters:: element – A value to update the drift detector with. Usually, this is the prediction error of a model.

cli_help() → str[source]#

detected_change() → bool[source]#: Is the detector currently detecting a concept drift?

detected_warning() → bool[source]#: Is the detector currently warning of an upcoming concept drift?

classmethod from_cli(cli: str) → MOADriftDetector[source]#

Create a detector instance configured from a MOA CLI string.

Parameters:: cli – Command-line style options string for MOA detector hyper-parameters.
Returns:: A new detector instance initialized with cli.

classmethod from_params( schema: Any = None, params: dict[str, Any] | None = None, random_seed: int = 1, ) → Any[source]#: Construct an instance from parameters produced by get_params.

get_params() → dict[str, Any][source]#: Return the hyper-parameters captured from the constructor.

reset(clean_history: bool = False) → None[source]#

Reset the drift detector.

Parameters:: clean_history – Whether to reset detection history, defaults to False

REQUIRES_FIT: bool = False#: If True, this detector needs a reference distribution before it can detect change. Concept drift detectors leave this as False and only use add_element().

CUSUM#

`CUSUM`#