Data
Loan_Approval_Status_Classification

Loan_Approval_Status_Classification

active ARFF CC BY 4.0 Visibility: public Uploaded 12-12-2024 by Yayun Li
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# Loan Approval Classification Dataset This dataset is a synthetic version inspired by the original Credit Risk dataset on Kaggle and enriched with additional variables based on historical loan approval data. SMOTENC was used to simulate new data points to enlarge the databank. The dataset is structured for both categorical and continuous features. ## Target Variable The target variable 'loan_status' is binary: - 1 = approved - 0 = rejected

24 features

loan_status (target)nominal2 unique values
0 missing
person_agenumeric60 unique values
0 missing
person_educationnumeric5 unique values
0 missing
person_incomenumeric33989 unique values
0 missing
person_emp_expnumeric63 unique values
0 missing
loan_amntnumeric4483 unique values
0 missing
loan_int_ratenumeric1302 unique values
0 missing
loan_percent_incomenumeric64 unique values
0 missing
cb_person_cred_hist_lengthnumeric29 unique values
0 missing
credit_scorenumeric340 unique values
0 missing
defaults_nonumeric2 unique values
0 missing
defaults_yesnumeric2 unique values
0 missing
gender_femalenumeric2 unique values
0 missing
gender_malenumeric2 unique values
0 missing
home_mortgagenumeric2 unique values
0 missing
home_othernumeric2 unique values
0 missing
home_ownnumeric2 unique values
0 missing
home_rentnumeric2 unique values
0 missing
intent_debtconsolidationnumeric2 unique values
0 missing
intent_educationnumeric2 unique values
0 missing
intent_homeimprovementnumeric2 unique values
0 missing
intent_medicalnumeric2 unique values
0 missing
intent_personalnumeric2 unique values
0 missing
intent_venturenumeric2 unique values
0 missing
Show all 24 features

19 properties

NumberOfInstances
45000
Number of instances (rows) of the dataset.
NumberOfFeatures
24
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
23
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
4.17
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
0.78
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
95.83
Percentage of numeric attributes.
MajorityClassPercentage
77.78
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
4.17
Percentage of nominal attributes.
MajorityClassSize
35000
Number of instances belonging to the most frequent class.
MinorityClassPercentage
22.22
Percentage of instances belonging to the least frequent class.
MinorityClassSize
10000
Number of instances belonging to the least frequent class.
Show all 19 properties

1 tasks

Supervised Classification on Loan_Approval_Status_Classification
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: loan_status
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