alibi_detect.cd.tensorflow.mmd module
- class alibi_detect.cd.tensorflow.mmd.MMDDriftTF(x_ref, p_val=0.05, x_ref_preprocessed=False, preprocess_at_init=True, update_x_ref=None, preprocess_fn=None, kernel=<class 'alibi_detect.utils.tensorflow.kernels.GaussianRBF'>, sigma=None, configure_kernel_from_x_ref=True, n_permutations=100, input_shape=None, data_type=None)[source]
Bases:
BaseMMDDrift- __init__(x_ref, p_val=0.05, x_ref_preprocessed=False, preprocess_at_init=True, update_x_ref=None, preprocess_fn=None, kernel=<class 'alibi_detect.utils.tensorflow.kernels.GaussianRBF'>, sigma=None, configure_kernel_from_x_ref=True, n_permutations=100, input_shape=None, data_type=None)[source]
Maximum Mean Discrepancy (MMD) data drift detector using a permutation test.
- Parameters:
x_ref (
Union[ndarray,list]) – Data used as reference distribution.p_val (
float) – p-value used for the significance of the permutation test.x_ref_preprocessed (
bool) – Whether the given reference data x_ref has been preprocessed yet. If x_ref_preprocessed=True, only the test data x will be preprocessed at prediction time. If x_ref_preprocessed=False, the reference data will also be preprocessed.preprocess_at_init (
bool) – Whether to preprocess the reference data when the detector is instantiated. Otherwise, the reference data will be preprocessed at prediction time. Only applies if x_ref_preprocessed=False.update_x_ref (
Optional[Dict[str,int]]) – Reference data can optionally be updated to the last n instances seen by the detector or via reservoir sampling with size n. For the former, the parameter equals {‘last’: n} while for reservoir sampling {‘reservoir_sampling’: n} is passed.preprocess_fn (
Optional[Callable]) – Function to preprocess the data before computing the data drift metrics.kernel (
Callable) – Kernel used for the MMD computation, defaults to Gaussian RBF kernel.sigma (
Optional[ndarray]) – Optionally set the GaussianRBF kernel bandwidth. Can also pass multiple bandwidth values as an array. The kernel evaluation is then averaged over those bandwidths.configure_kernel_from_x_ref (
bool) – Whether to already configure the kernel bandwidth from the reference data.n_permutations (
int) – Number of permutations used in the permutation test.data_type (
Optional[str]) – Optionally specify the data type (tabular, image or time-series). Added to metadata.
- kernel_matrix(x, y)[source]
Compute and return full kernel matrix between arrays x and y.
- Return type:
Tensor