aif360.datasets.BankDataset

class aif360.datasets.BankDataset(label_name='y', favorable_classes=['yes'], protected_attribute_names=['age'], privileged_classes=[<function BankDataset.<lambda>>], instance_weights_name=None, categorical_features=['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week', 'poutcome'], features_to_keep=[], features_to_drop=[], na_values=['unknown'], custom_preprocessing=None, metadata=None)[source]

Bank marketing Dataset.

See aif360/data/raw/bank/README.md.

See StandardDataset for a description of the arguments.

By default, this code converts the ‘age’ attribute to a binary value where privileged is age >= 25 and unprivileged is age < 25 as in GermanDataset.

Methods

align_datasets Align the other dataset features, labels and protected_attributes to this dataset.
convert_to_dataframe Convert the StructuredDataset to a pandas.DataFrame.
copy Convenience method to return a copy of this dataset.
export_dataset Export the dataset and supporting attributes TODO: The preferred file format is HDF
import_dataset Import the dataset and supporting attributes TODO: The preferred file format is HDF
split Split this dataset into multiple partitions.
subset Subset of dataset based on position :param indexes: iterable which contains row indexes
temporarily_ignore Temporarily add the fields provided to ignore_fields.
validate_dataset Error checking and type validation.
__init__(label_name='y', favorable_classes=['yes'], protected_attribute_names=['age'], privileged_classes=[<function BankDataset.<lambda>>], instance_weights_name=None, categorical_features=['job', 'marital', 'education', 'default', 'housing', 'loan', 'contact', 'month', 'day_of_week', 'poutcome'], features_to_keep=[], features_to_drop=[], na_values=['unknown'], custom_preprocessing=None, metadata=None)[source]

See StandardDataset for a description of the arguments.

By default, this code converts the ‘age’ attribute to a binary value where privileged is age >= 25 and unprivileged is age < 25 as in GermanDataset.