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.
So this is a Creditcard fraud detection classifier
This classifier can identify fraudulent credit card transactions.
You can use it by sending a python list [] which contains 30 nombers that represent ['Time of process', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10','V11', 'V12', 'V13', 'V14', 'V15', 'V16', 'V17', 'V18', 'V19', 'V20','V21', 'V22', 'V23', 'V24', 'V25', 'V26', 'V27', 'V28', 'Amount','Class']
Features V1, V2, … V28 are the principal components obtained with PCA
Unfortunately, due to confidentiality issues, we cannot provide the original features and more background information about the data
A sample of Fraud process is : [ 4.06000000e+02, -2.31222654e+00, 1.95199201e+00, -1.60985073e+00, 3.99790559e+00, -5.22187865e-01, -1.42654532e+00, -2.53738731e+00, 1.39165725e+00, -2.77008928e+00, -2.77227214e+00, 3.20203321e+00, -2.89990739e+00, -5.95221881e-01, -4.28925378e+00, 3.89724120e-01, -1.14074718e+00, -2.83005567e+00, -1.68224682e-02, 4.16955705e-01, 1.26910559e-01, 5.17232371e-01, -3.50493686e-02, -4.65211076e-01, 3.20198199e-01, 4.45191675e-02, 1.77839798e-01, 2.61145003e-01, -1.43275875e-01, 0.00000000e+00]
and the sample of Nonfraud process is : [0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,2,5,2,4,1,4,2,4,4,0,1]