--- dataset_info: features: - name: status of existing checking account dtype: class_label: names: '0': < 0 DM '1': 0 <= ... < 200 DM '2': '>= 200 DM / salary assignments for at least 1 year' '3': no checking account - name: duration in month dtype: float32 - name: credit history dtype: class_label: names: '0': no credits taken / all credits paid back duly '1': all credits at this bank paid back duly '2': existing credits paid back duly till now '3': delay in paying off in the past '4': critical account / other credits existing (not at this bank) - name: purpose dtype: class_label: names: '0': car (new) '1': car (used) '2': furniture/equipment '3': radio/television '4': domestic appliances '5': repairs '6': education '7': vacation '8': retraining '9': business '10': others - name: credit amount dtype: float32 - name: savings account/bonds dtype: class_label: names: '0': < 100 DM '1': 100 <= ... < 500 DM '2': 500 <= ... < 1000 DM '3': '>= 1000 DM' '4': unknown / no savings account - name: present employment since dtype: class_label: names: '0': unemployed '1': < 1 year '2': 1 <= ... < 4 years '3': 4 <= ... < 7 years '4': '>= 7 years' - name: installment rate in percentage of disposable income dtype: float32 - name: personal status and sex dtype: class_label: names: '0': 'male: divorced/separated' '1': 'female: divorced/separated/married' '2': 'male: single' '3': 'male: married/widowed' '4': 'female: single' - name: other debtors / guarantors dtype: class_label: names: '0': none '1': co-applicant '2': guarantor - name: present residence since dtype: float32 - name: property dtype: class_label: names: '0': real estate '1': building society savings agreement / life insurance '2': car or other, not in attribute 6 '3': unknown / no property - name: age in years dtype: float32 - name: other installment plans dtype: class_label: names: '0': bank '1': stores '2': none - name: housing dtype: class_label: names: '0': rent '1': own '2': for free - name: number of existing credits at this bank dtype: float32 - name: job dtype: class_label: names: '0': unemployed / unskilled - non-resident '1': unskilled - resident '2': skilled employee / official '3': management / self-employed / highly qualified employee / officer - name: number of people being liable to provide maintenance for dtype: float32 - name: telephone dtype: class_label: names: '0': none '1': yes, registered under the customer’s name - name: foreign worker dtype: class_label: names: '0': 'yes' '1': 'no' - name: class dtype: class_label: names: '0': good '1': bad splits: - name: train num_bytes: 140000 num_examples: 1000 download_size: 27173 dataset_size: 140000 configs: - config_name: default data_files: - split: train path: data/train-* ---