feature
stringclasses
12 values
original_value
stringlengths
3
4
encoded_value
int8
0
4
is_foreign
A201
0
is_foreign
A202
1
has_registered_phone_number
A191
0
has_registered_phone_number
A192
1
job_status
A171
0
job_status
A172
1
job_status
A173
2
job_status
A174
3
housing_status
A153
0
housing_status
A151
1
housing_status
A152
2
installment_plans
A141
0
installment_plans
A142
1
installment_plans
A143
2
guarantors
A101
0
guarantors
A102
1
guarantors
A103
2
marital_status
A91
0
marital_status
A92
0
marital_status
A93
1
marital_status
A94
2
marital_status
A95
1
sex
A91
0
sex
A93
0
sex
A94
0
sex
A92
1
sex
A95
1
employed_since
A71
0
employed_since
A72
1
employed_since
A73
2
employed_since
A74
3
employed_since
A75
4
current_savings
A65
0
current_savings
A61
1
current_savings
A62
2
current_savings
A63
3
current_savings
A64
4
credit_status
A30
0
credit_status
A31
1
credit_status
A32
2
credit_status
A33
3
credit_status
A34
4
checking_account_status
A14
0
checking_account_status
A11
1
checking_account_status
A12
2
checking_account_status
A13
3
YAML Metadata Error: "configs[0]" must be of type object
YAML Metadata Error: "configs[1]" must be of type object

German

The German dataset from the UCI ML repository. Dataset on loan grants to customers.

Configurations and tasks

Configuration Task Description
encoding Encoding dictionary showing original values of encoded features.
loan Binary classification Has the loan request been accepted?

Usage

from datasets import load_dataset

dataset = load_dataset("mstz/german", "loan")["train"]

Features

Feature Type
checking_account_status int8
account_life_in_months int8
credit_status int8
loan_purpose string
current_credit int32
current_savings int8
employed_since int8
installment_rate_percentage int8
sex int8
marital_status string
guarantors int8
years_living_in_current_residence int8
age int8
installment_plans string
housing_status int8
nr_credit_accounts_in_bank int8
job_status int8
number_of_people_in_support int8
has_registered_phone_number int8
is_foreign int8
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