german-credit / README.md
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metadata
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-*