alibi.utils.discretizer module

class alibi.utils.discretizer.Discretizer(data, numerical_features, feature_names, percentiles=(25, 50, 75))

Bases: object

__init__(data, numerical_features, feature_names, percentiles=(25, 50, 75))

Initialize the discretizer.

Parameters:

• data (ndarray) – Data to discretize.

• numerical_features (List[int]) – List of indices corresponding to the continuous feature columns. Only these features will be discretized.

• feature_names (List[str]) – List with feature names.

• percentiles (Sequence[Union[int, float]]) – Percentiles used for discretization.

bins(data)

Parameters:

data (ndarray) – Data to discretize.

Return type:

List[ndarray]

Returns:

List with bin values for each feature that is discretized.

discretize(data)

Parameters:

data (ndarray) – Data to discretize.

Return type:

ndarray

Returns:

Discretized version of data with the same dimension.

static get_percentiles(x, qts)

Discretizes the the data in x using the quantiles in qts. This is achieved by searching for the index of each value in x into qts, which is assumed to be a 1-D sorted array.

Parameters:

• x (ndarray) – A numpy array of data to be discretized

• qts (ndarray) – A numpy array of percentiles. This should be a 1-D array sorted in ascending order.

Return type:

ndarray

Returns:

A discretized data numpy array.