Data
Fraud-Detection-Updated)

Fraud-Detection-Updated)

active ARFF CC BY 4.0 Visibility: public Uploaded 13-11-2024 by Anna Wiewer
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Updated Fraud Detection dataset with nominal target for binary classification.

29 features

bad_flag (target)string2 unique values
0 missing
dpd_5_cntnumeric8 unique values
3481 missing
dpd_15_cntnumeric6 unique values
3481 missing
dpd_30_cntnumeric4 unique values
3481 missing
close_loans_cntnumeric21 unique values
15 missing
federal_district_nmnumeric9 unique values
0 missing
payment_type_0numeric9 unique values
0 missing
payment_type_1numeric28 unique values
0 missing
payment_type_2numeric26 unique values
0 missing
payment_type_3numeric24 unique values
0 missing
payment_type_4numeric7 unique values
0 missing
payment_type_5numeric1 unique values
0 missing
past_billings_cntnumeric21 unique values
248 missing
score_1numeric1274 unique values
649 missing
score_2numeric47 unique values
3917 missing
agenumeric51 unique values
0 missing
gendernumeric2 unique values
0 missing
rep_loan_date_yearnumeric3 unique values
0 missing
rep_loan_date_monthnumeric12 unique values
0 missing
rep_loan_date_daynumeric31 unique values
0 missing
rep_loan_date_weekdaynumeric7 unique values
0 missing
first_loan_yearnumeric2 unique values
0 missing
first_loan_monthnumeric12 unique values
0 missing
first_loan_daynumeric31 unique values
0 missing
first_loan_weekdaynumeric7 unique values
0 missing
first_overdue_date_yearnumeric2 unique values
3481 missing
first_overdue_date_monthnumeric12 unique values
3481 missing
first_overdue_date_daynumeric19 unique values
3481 missing
first_overdue_date_weekdaynumeric8 unique values
0 missing

19 properties

4156
Number of instances (rows) of the dataset.
29
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
25715
Number of missing values in the dataset.
4156
Number of instances with at least one value missing.
28
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
100
Percentage of instances having missing values.
21.34
Percentage of missing values.
1
Average class difference between consecutive instances.
96.55
Percentage of numeric attributes.
0.01
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
89.97
Percentage of instances belonging to the most frequent class.
3739
Number of instances belonging to the most frequent class.
10.03
Percentage of instances belonging to the least frequent class.
417
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 33% Holdout set - target_feature: bad_flag
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