Data
Credit_Approval_Classification

Credit_Approval_Classification

active ARFF CC BY 4.0 Visibility: public Uploaded 06-12-2024 by Anna Wiewer
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A dataset for binary classification of credit approval status. Features include customer demographics, financial attributes, and credit history. The target variable class indicates whether the credit is good or bad.

51 features

class (target)string2 unique values
0 missing
checking_statusnumeric4 unique values
0 missing
durationnumeric33 unique values
0 missing
credit_amountnumeric921 unique values
0 missing
savings_statusnumeric5 unique values
0 missing
employmentnumeric5 unique values
0 missing
installment_commitmentnumeric4 unique values
0 missing
residence_sincenumeric4 unique values
0 missing
agenumeric53 unique values
0 missing
existing_creditsnumeric4 unique values
0 missing
num_dependentsnumeric2 unique values
0 missing
credit_history_all paidnumeric2 unique values
0 missing
credit_history_critical/other existing creditnumeric2 unique values
0 missing
credit_history_delayed previouslynumeric2 unique values
0 missing
credit_history_existing paidnumeric2 unique values
0 missing
credit_history_no credits/all paidnumeric2 unique values
0 missing
purpose_businessnumeric2 unique values
0 missing
purpose_domestic appliancenumeric2 unique values
0 missing
purpose_educationnumeric2 unique values
0 missing
purpose_furniture/equipmentnumeric2 unique values
0 missing
purpose_new carnumeric2 unique values
0 missing
purpose_othernumeric2 unique values
0 missing
purpose_radio/tvnumeric2 unique values
0 missing
purpose_repairsnumeric2 unique values
0 missing
purpose_retrainingnumeric2 unique values
0 missing
purpose_used carnumeric2 unique values
0 missing
personal_status_female div/dep/marnumeric2 unique values
0 missing
personal_status_male div/sepnumeric2 unique values
0 missing
personal_status_male mar/widnumeric2 unique values
0 missing
personal_status_male singlenumeric2 unique values
0 missing
other_parties_co applicantnumeric2 unique values
0 missing
other_parties_guarantornumeric2 unique values
0 missing
other_parties_nonenumeric2 unique values
0 missing
property_magnitude_carnumeric2 unique values
0 missing
property_magnitude_life insurancenumeric2 unique values
0 missing
property_magnitude_no known propertynumeric2 unique values
0 missing
property_magnitude_real estatenumeric2 unique values
0 missing
other_payment_plans_banknumeric2 unique values
0 missing
other_payment_plans_nonenumeric2 unique values
0 missing
other_payment_plans_storesnumeric2 unique values
0 missing
housing_for freenumeric2 unique values
0 missing
housing_ownnumeric2 unique values
0 missing
housing_rentnumeric2 unique values
0 missing
job_high qualif/self emp/mgmtnumeric2 unique values
0 missing
job_skillednumeric2 unique values
0 missing
job_unemp/unskilled non resnumeric2 unique values
0 missing
job_unskilled residentnumeric2 unique values
0 missing
own_telephone_nonenumeric2 unique values
0 missing
own_telephone_yesnumeric2 unique values
0 missing
foreign_worker_nonumeric2 unique values
0 missing
foreign_worker_yesnumeric2 unique values
0 missing
Show all 51 features

19 properties

NumberOfInstances
1000
Number of instances (rows) of the dataset.
NumberOfFeatures
51
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
50
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
1
Average class difference between consecutive instances.
PercentageOfNumericFeatures
98.04
Percentage of numeric attributes.
Dimensionality
0.05
Number of attributes divided by the number of instances.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassPercentage
70
Percentage of instances belonging to the most frequent class.
MajorityClassSize
700
Number of instances belonging to the most frequent class.
MinorityClassPercentage
30
Percentage of instances belonging to the least frequent class.
MinorityClassSize
300
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
Show all 19 properties

1 tasks

Supervised Classification on Credit_Approval_Classification
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: class
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