Skip to main content
def Predictor.obs_stabilize(self, data, preprocess=False) [source]
Apply trained outlier detection and provide OUTLIER labels. Uses the outlier model trained during the pipeline to flag anomalous observations in new data.

​
Parameters

data : pDF
Input data of shape (n_samples, n_features).
 preprocess : bool
If True, accepts original columns and applies
fe_clean first. If False, expects output
from fe_clean / fe_stabilize.

​
Returns

ObsStabilizerResult