dataeval.detectors.drift.DriftMVDC¶

class dataeval.detectors.drift.DriftMVDC(n_folds=5, chunk_size=None, chunk_count=None, threshold=(0.45, 0.65))¶

Multivariant Domain Classifier

Parameters:¶

n_folds : int, default 5¶

Number of cross-validation (CV) folds.

chunk_size : int or None, default None¶

Number of samples in a chunk used in CV, will get one metric & prediction per chunk.

chunk_count : int or None, default None¶

Number of total chunks used in CV, will get one metric & prediction per chunk.

threshold : Tuple[float, float], default (0.45, 0.65)¶

(lower, upper) metric bounds on roc_auc for identifying drift.

fit(x_ref)¶

Fit the domain classifier on the training dataframe

Parameters:¶

x_ref : ArrayLike¶

Reference data with dim[n_samples, n_features].

Return type:¶

DriftMVDC

predict(x)¶

Perform inference on the test dataframe

Parameters:¶

x : ArrayLike¶

Test (analysis) data with dim[n_samples, n_features].

Return type:¶

DomainClassifierDriftResult