Fraud Detection - Credit Card
Fraud or genuine transaction
@kaggle.yashpaloswal_fraud_detection_credit_card
Fraud or genuine transaction
@kaggle.yashpaloswal_fraud_detection_credit_card
Content:-
The dataset contains all credit card transaction details.
Details:-
Except all columns class column denotes following:-
Class 0 --> Non fraudulent
class 1 --> fraudulent
Goal:-
The main goal is to build various different algos.
Solving method:-
The given problem statement is comes under binary classification
We have to solve problem using different machine learning algorithm as well as deep learning algorithms
CREATE TABLE creditcard (
"time" DOUBLE,
"v1" DOUBLE,
"v2" DOUBLE,
"v3" DOUBLE,
"v4" DOUBLE,
"v5" DOUBLE,
"v6" DOUBLE,
"v7" DOUBLE,
"v8" DOUBLE,
"v9" DOUBLE,
"v10" DOUBLE,
"v11" DOUBLE,
"v12" DOUBLE,
"v13" DOUBLE,
"v14" DOUBLE,
"v15" DOUBLE,
"v16" DOUBLE,
"v17" DOUBLE,
"v18" DOUBLE,
"v19" DOUBLE,
"v20" DOUBLE,
"v21" DOUBLE,
"v22" DOUBLE,
"v23" DOUBLE,
"v24" DOUBLE,
"v25" DOUBLE,
"v26" DOUBLE,
"v27" DOUBLE,
"v28" DOUBLE,
"amount" DOUBLE,
"class" BIGINT
);Anyone who has the link will be able to view this.