pysad.transform.probability_calibration.GaussianTailProbabilityCalibrator¶
- class pysad.transform.probability_calibration.GaussianTailProbabilityCalibrator(running_statistics=True, window_size=6400)[source]¶
Assuming that the scores follow normal distribution, this class provides an interface to convert the scores into probabilities via Q-function, i.e., the tail function of Gaussian distribution [BALPA17].
- Parameters:
Methods
__init__
([running_statistics, window_size])fit
(scores)Shortcut method that iteratively applies fit_partial to all instances in order.
fit_partial
(score)Fits particular (next) timestep's score to train the postprocessor.
fit_transform
(scores)Shortcut method that iteratively applies fit_transform_partial to all instances in order.
fit_transform_partial
(score)Shortcut method that iteratively applies fit_partial and transform_partial, respectively.
transform
(scores)Shortcut method that iteratively applies transform_partial to all instances in order.
transform_partial
(score)Transforms given score.
- fit(scores)¶
Shortcut method that iteratively applies fit_partial to all instances in order.
- Parameters:
shape (np.float64 array of) – Input scores.
- Returns:
self.
- Return type:
- fit_transform(scores)¶
Shortcut method that iteratively applies fit_transform_partial to all instances in order.
- Parameters:
shape (np.float64 array of) – Input scores.
- Returns:
Processed scores.
- Return type:
np.float64 array of shape (num_instances,)
- fit_transform_partial(score)¶
Shortcut method that iteratively applies fit_partial and transform_partial, respectively.
- transform(scores)¶
Shortcut method that iteratively applies transform_partial to all instances in order.
- Parameters:
shape (np.float64 array of) – Input scores.
- Returns:
Processed scores.
- Return type:
np.float64 array of shape (num_instances,)