Data
Credit_Card_Fraud_Detection

Credit_Card_Fraud_Detection

active ARFF Unknown Visibility: public Uploaded 05-10-2022 by louis geiler
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It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.

31 features

Class (target)numeric2 unique values
0 missing
Timenumeric124592 unique values
0 missing
V1numeric275663 unique values
0 missing
V2numeric275663 unique values
0 missing
V3numeric275663 unique values
0 missing
V4numeric275663 unique values
0 missing
V5numeric275663 unique values
0 missing
V6numeric275663 unique values
0 missing
V7numeric275663 unique values
0 missing
V8numeric275663 unique values
0 missing
V9numeric275663 unique values
0 missing
V10numeric275663 unique values
0 missing
V11numeric275663 unique values
0 missing
V12numeric275663 unique values
0 missing
V13numeric275663 unique values
0 missing
V14numeric275663 unique values
0 missing
V15numeric275663 unique values
0 missing
V16numeric275663 unique values
0 missing
V17numeric275663 unique values
0 missing
V18numeric275663 unique values
0 missing
V19numeric275663 unique values
0 missing
V20numeric275663 unique values
0 missing
V21numeric275663 unique values
0 missing
V22numeric275663 unique values
0 missing
V23numeric275663 unique values
0 missing
V24numeric275663 unique values
0 missing
V25numeric275663 unique values
0 missing
V26numeric275663 unique values
0 missing
V27numeric275663 unique values
0 missing
V28numeric275663 unique values
0 missing
Amountnumeric32767 unique values
0 missing

19 properties

284807
Number of instances (rows) of the dataset.
31
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.
31
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
100
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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