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---
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-*
---
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