Data
GermanCreditData

GermanCreditData

active ARFF Publicly available Visibility: public Uploaded 12-11-2024 by Niall Gagan
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German credit dataset, similar to original one, just age and gender are two different attributes. More info on the dataset here: https://archive.ics.uci.edu/dataset/144/statlog+german+credit+data

22 features

target (target)numeric2 unique values
0 missing
Unnamed: 0numeric1000 unique values
0 missing
acc_statusstring4 unique values
0 missing
acc_durationnumeric33 unique values
0 missing
credit_historystring5 unique values
0 missing
purposestring10 unique values
0 missing
credit_amountnumeric921 unique values
0 missing
savings_accstring5 unique values
0 missing
employment_timestring5 unique values
0 missing
installment_ratenumeric4 unique values
0 missing
genderstring2 unique values
0 missing
other_debtorsstring3 unique values
0 missing
residence_timenumeric4 unique values
0 missing
propertystring4 unique values
0 missing
agenumeric53 unique values
0 missing
installment_plansstring3 unique values
0 missing
housingstring3 unique values
0 missing
num_credits_at_banknumeric4 unique values
0 missing
jobstring4 unique values
0 missing
num_people_maintenancenumeric2 unique values
0 missing
phonestring2 unique values
0 missing
foreignerstring2 unique values
0 missing

19 properties

1000
Number of instances (rows) of the dataset.
22
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
9
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.58
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
40.91
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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