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credit-g

active ARFF Publicly available Visibility: public Uploaded 27-01-2023 by Young Lee
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This dataset classifies people described by a set of attributes as good or bad credit risks.This dataset comes with a cost matrix:Good Bad (predicted) Good 0 1 (actual)Bad 5 0 It is worse to class a customer as good when they are bad (5), than it is to class a customer as bad when they are good (1).

21 features

class (target)	string	2 unique values 0 missing
duration	numeric	33 unique values 0 missing
credit_amount	numeric	921 unique values 0 missing
installment_commitment	numeric	4 unique values 0 missing
residence_since	numeric	4 unique values 0 missing
age	numeric	53 unique values 0 missing
existing_credits	numeric	4 unique values 0 missing
num_dependents	numeric	2 unique values 0 missing
checking_status	nominal	4 unique values 0 missing
credit_history	nominal	5 unique values 0 missing
purpose	nominal	10 unique values 0 missing
savings_status	nominal	5 unique values 0 missing
employment	nominal	5 unique values 0 missing
personal_status	nominal	4 unique values 0 missing
other_parties	nominal	3 unique values 0 missing
property_magnitude	nominal	4 unique values 0 missing
other_payment_plans	nominal	3 unique values 0 missing
housing	nominal	3 unique values 0 missing
job	nominal	4 unique values 0 missing
own_telephone	nominal	2 unique values 0 missing
foreign_worker	nominal	2 unique values 0 missing